paper_id stringlengths 10 10 | paper_url stringlengths 37 80 | title stringlengths 4 518 | abstract stringlengths 3 7.27k | arxiv_id stringlengths 9 16 ⌀ | url_abs stringlengths 18 601 | url_pdf stringlengths 21 601 | aspect_tasks list | aspect_methods list | aspect_datasets list |
|---|---|---|---|---|---|---|---|---|---|
B32MV46FTA | https://paperswithcode.com/paper/efficient-machine-learning-for-large-scale | Efficient Machine Learning for Large-Scale Urban Land-Use Forecasting in Sub-Saharan Africa | Urbanization is a common phenomenon in developing countries and it poses serious challenges when not managed effectively. Lack of proper planning and management may cause the encroachment of urban fabrics into reserved or special regions which in turn can lead to an unsustainable increase in population. Ineffective man... | 1908.00340 | https://arxiv.org/abs/1908.00340v1 | https://arxiv.org/pdf/1908.00340v1.pdf | [
"Decision Making"
] | [] | [] |
jhB8you7CK | https://paperswithcode.com/paper/one-step-regression-and-classification-with | One-step regression and classification with crosspoint resistive memory arrays | Machine learning has been getting a large attention in the recent years, as a tool to process big data generated by ubiquitous sensors in our daily life. High speed, low energy computing machines are in demand to enable real-time artificial intelligence at the edge, i.e., without the support of a remote frame server in... | 2005.01988 | https://arxiv.org/abs/2005.01988v1 | https://arxiv.org/pdf/2005.01988v1.pdf | [] | [
"Logistic Regression",
"Linear Regression"
] | [] |
CAWVGbbavA | https://paperswithcode.com/paper/moralstrength-exploiting-a-moral-lexicon-and | MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations Prediction | Moral rhetoric plays a fundamental role in how we perceive and interpret the information we receive, greatly influencing our decision-making process. Especially when it comes to controversial social and political issues, our opinions and attitudes are hardly ever based on evidence alone. The Moral Foundations Dictionar... | 1904.08314 | https://arxiv.org/abs/1904.08314v2 | https://arxiv.org/pdf/1904.08314v2.pdf | [
"Decision Making",
"Semantic Similarity",
"Semantic Textual Similarity",
"Word Embeddings"
] | [
"Logistic Regression"
] | [] |
Q3OdGFEDxn | https://paperswithcode.com/paper/gtea-representation-learning-for-temporal | GTEA: Representation Learning for Temporal Interaction Graphs via Edge Aggregation | We consider the problem of representation learning for temporal interaction graphs where a network of entities with complex interactions over an extended period of time is modeled as a graph with a rich set of node and edge attributes. In particular, an edge between a node-pair within the graph corresponds to a multi-d... | 2009.05266 | https://arxiv.org/abs/2009.05266v2 | https://arxiv.org/pdf/2009.05266v2.pdf | [
"Node Classification",
"Representation Learning",
"Time Series"
] | [
"Sigmoid Activation",
"Layer Normalization",
"Tanh Activation",
"LSTM",
"Dropout",
"Dense Connections",
"BPE",
"Label Smoothing",
"Multi-Head Attention",
"Scaled Dot-Product Attention",
"Adam",
"Residual Connection",
"Softmax",
"Transformer"
] | [] |
xz7K7I57fc | https://paperswithcode.com/paper/sygus-comp-2017-results-and-analysis | SyGuS-Comp 2017: Results and Analysis | Syntax-Guided Synthesis (SyGuS) is the computational problem of finding an
implementation f that meets both a semantic constraint given by a logical
formula phi in a background theory T, and a syntactic constraint given by a
grammar G, which specifies the allowed set of candidate implementations. Such a
synthesis probl... | 1711.11438 | http://arxiv.org/abs/1711.11438v1 | http://arxiv.org/pdf/1711.11438v1.pdf | [] | [] | [] |
52bZPrRFsI | https://paperswithcode.com/paper/using-semantic-web-services-for-ai-based | Using Semantic Web Services for AI-Based Research in Industry 4.0 | The transition to Industry 4.0 requires smart manufacturing systems that are easily configurable and provide a high level of flexibility during manufacturing in order to achieve mass customization or to support cloud manufacturing. To realize this, Cyber-Physical Systems (CPSs) combined with Artificial Intelligence (AI... | 2007.03580 | https://arxiv.org/abs/2007.03580v1 | https://arxiv.org/pdf/2007.03580v1.pdf | [] | [] | [] |
voGphl1I9e | https://paperswithcode.com/paper/resource-planning-for-rescue-operations | Resource Planning For Rescue Operations | After an earthquake, disaster sites pose a multitude of health and safety
concerns. A rescue operation of people trapped in the ruins after an earthquake
disaster requires a series of intelligent behavior, including planning. For a
successful rescue operation, given a limited number of available actions and
regulations... | 1607.03979 | http://arxiv.org/abs/1607.03979v1 | http://arxiv.org/pdf/1607.03979v1.pdf | [] | [] | [] |
j3L_k1jDLS | https://paperswithcode.com/paper/deep-convolutional-neural-networks-with-merge | Deep Convolutional Neural Networks with Merge-and-Run Mappings | A deep residual network, built by stacking a sequence of residual blocks, is
easy to train, because identity mappings skip residual branches and thus
improve information flow. To further reduce the training difficulty, we present
a simple network architecture, deep merge-and-run neural networks. The novelty
lies in a m... | 1611.07718 | http://arxiv.org/abs/1611.07718v2 | http://arxiv.org/pdf/1611.07718v2.pdf | [] | [] | [] |
jr5dBQiiDK | https://paperswithcode.com/paper/an-experimental-study-on-implicit-social | An experimental study on implicit social recommendation | Social recommendation problems have drawn a lot of attention recently due to the prevalence of social networking
sites. The experiments in previous literature suggest that
social information is very effective in improving traditional
recommendation algorithms. However, explicit social information is not always avail... | null | https://wing.comp.nus.edu.sg/~wing.nus/sig/papers_ir/p73.pdf | https://wing.comp.nus.edu.sg/~wing.nus/sig/papers_ir/p73.pdf | [
"Recommendation Systems"
] | [] | [] |
RQgt-c-QGI | https://paperswithcode.com/paper/nonparametric-sparse-hierarchical-models | Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images | We propose a novel hierarchical, nonlinear model that predicts brain activity in area V1 evoked by natural images. In the study reported here brain activity was measured by means of functional magnetic resonance imaging (fMRI), a noninvasive technique that provides an indirect measure of neural activity pooled over a s... | null | http://papers.nips.cc/paper/3481-nonparametric-sparse-hierarchical-models-describe-v1-fmri-responses-to-natural-images | http://papers.nips.cc/paper/3481-nonparametric-sparse-hierarchical-models-describe-v1-fmri-responses-to-natural-images.pdf | [] | [] | [] |
OQWhn_ChJk | https://paperswithcode.com/paper/representation-and-interchange-of-linguistic | Representation and Interchange of Linguistic Annotation. An In-Depth, Side-by-Side Comparison of Three Designs | For decades, most self-respecting linguistic engineering initiatives have designed and implemented custom representations for various layers of, for example, morphological, syntactic, and semantic analysis. Despite occasional efforts at harmonization or even standardization, our field today is blessed with a multitude ... | null | https://www.aclweb.org/anthology/W17-0808/ | https://www.aclweb.org/anthology/W17-0808 | [] | [] | [] |
czaZYXZYwh | https://paperswithcode.com/paper/the-boosted-dc-algorithm-for-nonsmooth | The Boosted DC Algorithm for nonsmooth functions | The Boosted Difference of Convex functions Algorithm (BDCA) was recently proposed for minimizing smooth difference of convex (DC) functions. BDCA accelerates the convergence of the classical Difference of Convex functions Algorithm (DCA) thanks to an additional line search step. The purpose of this paper is twofold. Fi... | 1812.06070 | https://arxiv.org/abs/1812.06070v2 | https://arxiv.org/pdf/1812.06070v2.pdf | [] | [
"LINE"
] | [] |
_8rjgNnA7I | https://paperswithcode.com/paper/the-d-ans-corpus-the-dublin-autonomous | The D-ANS corpus: the Dublin-Autonomous Nervous System corpus of biosignal and multimodal recordings of conversational speech | Biosignals, such as electrodermal activity (EDA) and heart rate, are increasingly being considered as potential data sources to provide information about the temporal fluctuations in affective experience during human interaction. This paper describes an English-speaking, multiple session corpus of small groups of peopl... | null | https://www.aclweb.org/anthology/L14-1322/ | http://www.lrec-conf.org/proceedings/lrec2014/pdf/374_Paper.pdf | [] | [] | [] |
3qotoBW_vb | https://paperswithcode.com/paper/on-tighter-generalization-bound-for-deep | On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond | We establish a margin based data dependent generalization error bound for a general family of deep neural networks in terms of the depth and width, as well as the Jacobian of the networks. Through introducing a new characterization of the Lipschitz properties of neural network family, we achieve significantly tighter g... | 1806.05159 | https://arxiv.org/abs/1806.05159v4 | https://arxiv.org/pdf/1806.05159v4.pdf | [] | [] | [] |
2nBfdJ2xd0 | https://paperswithcode.com/paper/avoiding-undesired-choices-using-intelligent | Avoiding Undesired Choices Using Intelligent Adaptive Systems | We propose a number of heuristics that can be used for identifying when
intransitive choice behaviour is likely to occur in choice situations. We also
suggest two methods for avoiding undesired choice behaviour, namely transparent
communication and adaptive choice-set generation. We believe that these two
ways can cont... | 1404.3659 | http://arxiv.org/abs/1404.3659v1 | http://arxiv.org/pdf/1404.3659v1.pdf | [] | [] | [] |
g-EGPltD3j | https://paperswithcode.com/paper/proactive-intention-recognition-for-joint | Proactive Intention Recognition for Joint Human-Robot Search and Rescue Missions through Monte-Carlo Planning in POMDP Environments | Proactively perceiving others' intentions is a crucial skill to effectively interact in unstructured, dynamic and novel environments. This work proposes a first step towards embedding this skill in support robots for search and rescue missions. Predicting the responders' intentions, indeed, will enable exploration appr... | 1908.10125 | https://arxiv.org/abs/1908.10125v1 | https://arxiv.org/pdf/1908.10125v1.pdf | [
"Intent Detection"
] | [] | [] |
5X0E8DebKs | https://paperswithcode.com/paper/high-dimensional-multivariate-forecasting | High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes | Predicting the dependencies between observations from multiple time series is critical for applications such as anomaly detection, financial risk management, causal analysis, or demand forecasting. However, the computational and numerical difficulties of estimating time-varying and high-dimensional covariance matrices ... | 1910.03002 | https://arxiv.org/abs/1910.03002v2 | https://arxiv.org/pdf/1910.03002v2.pdf | [
"Anomaly Detection",
"Time Series"
] | [] | [] |
bNhsiwavuN | https://paperswithcode.com/paper/local-algorithms-for-interactive-clustering | Local algorithms for interactive clustering | We study the design of interactive clustering algorithms for data sets
satisfying natural stability assumptions. Our algorithms start with any initial
clustering and only make local changes in each step; both are desirable
features in many applications. We show that in this constrained setting one can
still design prov... | 1312.6724 | http://arxiv.org/abs/1312.6724v3 | http://arxiv.org/pdf/1312.6724v3.pdf | [] | [] | [] |
CtZVVzfXJs | https://paperswithcode.com/paper/a-bag-of-visual-words-approach-for-symbols | A Bag of Visual Words Approach for Symbols-Based Coarse-Grained Ancient Coin Classification | The field of Numismatics provides the names and descriptions of the symbols
minted on the ancient coins. Classification of the ancient coins aims at
assigning a given coin to its issuer. Various issuers used various symbols for
their coins. We propose to use these symbols for a framework that will coarsely
classify the... | 1304.6192 | http://arxiv.org/abs/1304.6192v1 | http://arxiv.org/pdf/1304.6192v1.pdf | [
"Scene Recognition"
] | [] | [] |
BGX9kBCG3U | https://paperswithcode.com/paper/classification-of-diabetic-retinopathy-via | Classification of Diabetic Retinopathy via Fundus Photography: Utilization of Deep Learning Approaches to Speed up Disease Detection | In this paper, we propose two distinct solutions to the problem of Diabetic Retinopathy (DR) classification. In the first approach, we introduce a shallow neural network architecture. This model performs well on classification of the most frequent classes while fails at classifying the less frequent ones. In the second... | 2007.09478 | https://arxiv.org/abs/2007.09478v1 | https://arxiv.org/pdf/2007.09478v1.pdf | [
"Transfer Learning"
] | [] | [] |
BgXOUem8lY | https://paperswithcode.com/paper/dynamic-models-applied-to-value-learning-in | Dynamic Models Applied to Value Learning in Artificial Intelligence | Experts in Artificial Intelligence (AI) development predict that advances in the development of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance is not made prudently and critically-reflexively, it can result in negative outcomes for humanity. For this reason, sev... | 2005.05538 | https://arxiv.org/abs/2005.05538v3 | https://arxiv.org/pdf/2005.05538v3.pdf | [] | [] | [] |
e6_tUzSbp4 | https://paperswithcode.com/paper/convolutional-recurrent-neural-networks-for-2 | Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting | Keyword spotting (KWS) constitutes a major component of human-technology
interfaces. Maximizing the detection accuracy at a low false alarm (FA) rate,
while minimizing the footprint size, latency and complexity are the goals for
KWS. Towards achieving them, we study Convolutional Recurrent Neural Networks
(CRNNs). Insp... | 1703.05390 | http://arxiv.org/abs/1703.05390v3 | http://arxiv.org/pdf/1703.05390v3.pdf | [
"Keyword Spotting",
"Small-Footprint Keyword Spotting",
"Speech Recognition"
] | [] | [] |
tFXyw-OuS6 | https://paperswithcode.com/paper/accelerated-inference-for-latent-variable | Accelerated Parallel Non-conjugate Sampling for Bayesian Non-parametric Models | Inference of latent feature models in the Bayesian nonparametric setting is generally difficult, especially in high dimensional settings, because it usually requires proposing features from some prior distribution. In special cases, where the integration is tractable, we could sample new feature assignments according t... | 1705.07178 | https://arxiv.org/abs/1705.07178v4 | https://arxiv.org/pdf/1705.07178v4.pdf | [
"Bayesian Inference"
] | [] | [] |
rVNkw7fy28 | https://paperswithcode.com/paper/matching-pursuit-lasso-part-ii-applications | Matching Pursuit LASSO Part II: Applications and Sparse Recovery over Batch Signals | Matching Pursuit LASSIn Part I \cite{TanPMLPart1}, a Matching Pursuit LASSO
({MPL}) algorithm has been presented for solving large-scale sparse recovery
(SR) problems. In this paper, we present a subspace search to further improve
the performance of MPL, and then continue to address another major challenge of
SR -- bat... | 1302.5010 | http://arxiv.org/abs/1302.5010v2 | http://arxiv.org/pdf/1302.5010v2.pdf | [
"Compressive Sensing",
"Face Recognition"
] | [] | [] |
49RNCrp1KA | https://paperswithcode.com/paper/the-distribution-family-of-similarity | The Distribution Family of Similarity Distances | Assessing similarity between features is a key step in object recognition and scene categorization tasks. We argue that knowledge on the distribution of distances generated by similarity functions is crucial in deciding whether features are similar or not. Intuitively one would expect that similarities between features... | null | http://papers.nips.cc/paper/3367-the-distribution-family-of-similarity-distances | http://papers.nips.cc/paper/3367-the-distribution-family-of-similarity-distances.pdf | [
"Object Recognition",
"Scene Recognition"
] | [] | [] |
RLfk9OdxY3 | https://paperswithcode.com/paper/projectron-a-shallow-and-interpretable | Projectron -- A Shallow and Interpretable Network for Classifying Medical Images | This paper introduces the `Projectron' as a new neural network architecture
that uses Radon projections to both classify and represent medical images. The
motivation is to build shallow networks which are more interpretable in the
medical imaging domain. Radon transform is an established technique that can
reconstruct ... | 1904.00740 | http://arxiv.org/abs/1904.00740v1 | http://arxiv.org/pdf/1904.00740v1.pdf | [] | [] | [] |
pvAWHtmskU | https://paperswithcode.com/paper/cross-modal-health-state-estimation | Cross-Modal Health State Estimation | Individuals create and consume more diverse data about themselves today than
any time in history. Sources of this data include wearable devices, images,
social media, geospatial information and more. A tremendous opportunity rests
within cross-modal data analysis that leverages existing domain knowledge
methods to unde... | 1808.06462 | http://arxiv.org/abs/1808.06462v2 | http://arxiv.org/pdf/1808.06462v2.pdf | [
"Decision Making"
] | [] | [] |
dl0REi2Hpr | https://paperswithcode.com/paper/ctap-a-web-based-tool-supporting-automatic | CTAP: A Web-Based Tool Supporting Automatic Complexity Analysis | Informed by research on readability and language acquisition, computational linguists have developed sophisticated tools for the analysis of linguistic complexity. While some tools are starting to become accessible on the web, there still is a disconnect between the features that can in principle be identified based on... | null | https://www.aclweb.org/anthology/W16-4113/ | https://www.aclweb.org/anthology/W16-4113 | [
"Language Acquisition"
] | [] | [] |
nQKFg0ND34 | https://paperswithcode.com/paper/plasticity-enhanced-domain-wall-mtj-neural | Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning | Machine learning implements backpropagation via abundant training samples. We demonstrate a multi-stage learning system realized by a promising non-volatile memory device, the domain-wall magnetic tunnel junction (DW-MTJ). The system consists of unsupervised (clustering) as well as supervised sub-systems, and generaliz... | 2003.02357 | https://arxiv.org/abs/2003.02357v1 | https://arxiv.org/pdf/2003.02357v1.pdf | [] | [] | [] |
CK25pituoU | https://paperswithcode.com/paper/mirror-surface-reconstruction-under-an | Mirror Surface Reconstruction Under an Uncalibrated Camera | This paper addresses the problem of mirror surface reconstruction, and a solution based on observing the reflections of a moving reference plane on the mirror surface is proposed. Unlike previous approaches which require tedious work to calibrate the camera, our method can recover both the camera intrinsics and extrins... | null | http://openaccess.thecvf.com/content_cvpr_2016/html/Han_Mirror_Surface_Reconstruction_CVPR_2016_paper.html | http://openaccess.thecvf.com/content_cvpr_2016/papers/Han_Mirror_Surface_Reconstruction_CVPR_2016_paper.pdf | [] | [
"LINE"
] | [] |
eAvmEeylF_ | https://paperswithcode.com/paper/write-a-classifier-predicting-visual | Write a Classifier: Predicting Visual Classifiers from Unstructured Text | People typically learn through exposure to visual concepts associated with
linguistic descriptions. For instance, teaching visual object categories to
children is often accompanied by descriptions in text or speech. In a machine
learning context, these observations motivates us to ask whether this learning
process coul... | 1601.00025 | http://arxiv.org/abs/1601.00025v2 | http://arxiv.org/pdf/1601.00025v2.pdf | [
"Transfer Learning"
] | [] | [] |
EZO34JeWW0 | https://paperswithcode.com/paper/higher-order-projected-power-iterations-for | Higher-order Projected Power Iterations for Scalable Multi-Matching | The matching of multiple objects (e.g. shapes or images) is a fundamental
problem in vision and graphics. In order to robustly handle ambiguities, noise
and repetitive patterns in challenging real-world settings, it is essential to
take geometric consistency between points into account. Computationally, the
multi-match... | 1811.10541 | http://arxiv.org/abs/1811.10541v2 | http://arxiv.org/pdf/1811.10541v2.pdf | [] | [] | [] |
iGMWDmaGLR | https://paperswithcode.com/paper/optimal-bipartite-network-clustering | Optimal Bipartite Network Clustering | We study bipartite community detection in networks, or more generally the
network biclustering problem. We present a fast two-stage procedure based on
spectral initialization followed by the application of a pseudo-likelihood
classifier twice. Under mild regularity conditions, we establish the weak
consistency of the p... | 1803.06031 | http://arxiv.org/abs/1803.06031v2 | http://arxiv.org/pdf/1803.06031v2.pdf | [
"Community Detection"
] | [] | [] |
lZWcIK9FE9 | https://paperswithcode.com/paper/a-robust-visual-system-for-small-target | A Robust Visual System for Small Target Motion Detection Against Cluttered Moving Backgrounds | Monitoring small objects against cluttered moving backgrounds is a huge
challenge to future robotic vision systems. As a source of inspiration, insects
are quite apt at searching for mates and tracking prey -- which always appear
as small dim speckles in the visual field. The exquisite sensitivity of insects
for small ... | 1904.04363 | http://arxiv.org/abs/1904.04363v1 | http://arxiv.org/pdf/1904.04363v1.pdf | [
"Motion Detection"
] | [] | [] |
38Od8ZMYiI | https://paperswithcode.com/paper/capturing-the-diversity-of-biological-tuning | Capturing the diversity of biological tuning curves using generative adversarial networks | Tuning curves characterizing the response selectivities of biological neurons
often exhibit large degrees of irregularity and diversity across neurons.
Theoretical network models that feature heterogeneous cell populations or
random connectivity also give rise to diverse tuning curves. However, a general
framework for ... | 1707.04582 | http://arxiv.org/abs/1707.04582v3 | http://arxiv.org/pdf/1707.04582v3.pdf | [] | [] | [] |
pWpFZEmHIg | https://paperswithcode.com/paper/robustness-of-sentence-length-measures-in | Robustness of sentence length measures in written texts | Hidden structural patterns in written texts have been subject of considerable
research in the last decades. In particular, mapping a text into a time series
of sentence lengths is a natural way to investigate text structure. Typically,
sentence length has been quantified by using measures based on the number of
words a... | 1805.01460 | http://arxiv.org/abs/1805.01460v1 | http://arxiv.org/pdf/1805.01460v1.pdf | [
"Lemmatization",
"Time Series"
] | [] | [] |
6rqCRQPqTk | https://paperswithcode.com/paper/a-study-of-compositional-generalization-in | A Study of Compositional Generalization in Neural Models | Compositional and relational learning is a hallmark of human intelligence, but one which presents challenges for neural models. One difficulty in the development of such models is the lack of benchmarks with clear compositional and relational task structure on which to systematically evaluate them. In this paper, we in... | 2006.09437 | https://arxiv.org/abs/2006.09437v2 | https://arxiv.org/pdf/2006.09437v2.pdf | [
"Image Classification",
"Relational Reasoning"
] | [
"1x1 Convolution",
"ReLU",
"Bottleneck Residual Block",
"Batch Normalization",
"Average Pooling",
"Max Pooling",
"Global Average Pooling",
"Residual Connection",
"Kaiming Initialization",
"Convolution",
"Residual Block",
"ResNet"
] | [] |
DAUd-HbzP1 | https://paperswithcode.com/paper/learning-like-humans-with-deep-symbolic | Learning like humans with Deep Symbolic Networks | We introduce the Deep Symbolic Network (DSN) model, which aims at becoming
the white-box version of Deep Neural Networks (DNN). The DSN model provides a
simple, universal yet powerful structure, similar to DNN, to represent any
knowledge of the world, which is transparent to humans. The conjecture behind
the DSN model ... | 1707.03377 | http://arxiv.org/abs/1707.03377v2 | http://arxiv.org/pdf/1707.03377v2.pdf | [
"Small Data Image Classification"
] | [] | [] |
yMZ18WUzAv | https://paperswithcode.com/paper/topological-defects-and-confinement-with | Topological defects and confinement with machine learning: the case of monopoles in compact electrodynamics | We investigate the advantages of machine learning techniques to recognize the dynamics of topological objects in quantum field theories. We consider the compact U(1) gauge theory in three spacetime dimensions as the simplest example of a theory that exhibits confinement and mass gap phenomena generated by monopoles. We... | 2006.09113 | https://arxiv.org/abs/2006.09113v1 | https://arxiv.org/pdf/2006.09113v1.pdf | [] | [] | [] |
G79vNnKuO3 | https://paperswithcode.com/paper/machine-learning-and-big-scientific-data | Machine Learning and Big Scientific Data | This paper reviews some of the challenges posed by the huge growth of experimental data generated by the new generation of large-scale experiments at UK national facilities at the Rutherford Appleton Laboratory site at Harwell near Oxford. Such "Big Scientific Data" comes from the Diamond Light Source and Electron Micr... | 1910.07631 | https://arxiv.org/abs/1910.07631v1 | https://arxiv.org/pdf/1910.07631v1.pdf | [
"Electron Microscopy",
"Object Recognition"
] | [] | [] |
hLlpBFykda | https://paperswithcode.com/paper/fleet-size-and-mix-split-delivery-vehicle | Fleet Size and Mix Split-Delivery Vehicle Routing | In the classic Vehicle Routing Problem (VRP) a fleet of of vehicles has to
visit a set of customers while minimising the operations' costs. We study a
rich variant of the VRP featuring split deliveries, an heterogeneous fleet, and
vehicle-commodity incompatibility constraints. Our goal is twofold: define the
cheapest r... | 1612.01691 | http://arxiv.org/abs/1612.01691v1 | http://arxiv.org/pdf/1612.01691v1.pdf | [] | [] | [] |
X39c-oXt8O | https://paperswithcode.com/paper/real-time-plant-health-assessment-via | Real-time Plant Health Assessment Via Implementing Cloud-based Scalable Transfer Learning On AWS DeepLens | In the Agriculture sector, control of plant leaf diseases is crucial as it influences the quality and production of plant species with an impact on the economy of any country. Therefore, automated identification and classification of plant leaf disease at an early stage is essential to reduce economic loss and to conse... | 2009.04110 | https://arxiv.org/abs/2009.04110v2 | https://arxiv.org/pdf/2009.04110v2.pdf | [
"Transfer Learning"
] | [] | [] |
2OoHmqu-bf | https://paperswithcode.com/paper/variational-inference-over-non-differentiable | Variational Inference over Non-differentiable Cardiac Simulators using Bayesian Optimization | Performing inference over simulators is generally intractable as their
runtime means we cannot compute a marginal likelihood. We develop a
likelihood-free inference method to infer parameters for a cardiac simulator,
which replicates electrical flow through the heart to the body surface. We
improve the fit of a state-o... | 1712.03353 | http://arxiv.org/abs/1712.03353v1 | http://arxiv.org/pdf/1712.03353v1.pdf | [
"Variational Inference"
] | [] | [] |
WyeetBIX3H | https://paperswithcode.com/paper/pac-bayesian-auc-classification-and-scoring | PAC-Bayesian AUC classification and scoring | We develop a scoring and classification procedure based on the PAC-Bayesian
approach and the AUC (Area Under Curve) criterion. We focus initially on the
class of linear score functions. We derive PAC-Bayesian non-asymptotic bounds
for two types of prior for the score parameters: a Gaussian prior, and a
spike-and-slab p... | 1410.1771 | http://arxiv.org/abs/1410.1771v2 | http://arxiv.org/pdf/1410.1771v2.pdf | [
"Feature Selection"
] | [] | [] |
SKhUaa7_DY | https://paperswithcode.com/paper/arabic-segmentation-combination-strategies | Arabic-Segmentation Combination Strategies for Statistical Machine Translation | Arabic segmentation was already applied successfully for the task of statistical machine translation (SMT). Yet, there is no consistent comparison of the effect of different techniques and methods over the final translation quality. In this work, we use existing tools and further re-implement and develop new methods fo... | null | https://www.aclweb.org/anthology/L12-1279/ | http://www.lrec-conf.org/proceedings/lrec2012/pdf/509_Paper.pdf | [
"Machine Translation"
] | [] | [] |
eeiXs8OOvJ | https://paperswithcode.com/paper/single-shot-6d-object-pose-estimation | Single Shot 6D Object Pose Estimation | In this paper, we introduce a novel single shot approach for 6D object pose estimation of rigid objects based on depth images. For this purpose, a fully convolutional neural network is employed, where the 3D input data is spatially discretized and pose estimation is considered as a regression task that is solved locall... | 2004.12729 | https://arxiv.org/abs/2004.12729v1 | https://arxiv.org/pdf/2004.12729v1.pdf | [
"6D Pose Estimation using RGB",
"Pose Estimation"
] | [] | [] |
fAi67idBGS | https://paperswithcode.com/paper/inherent-weight-normalization-in-stochastic | Inherent Weight Normalization in Stochastic Neural Networks | Multiplicative stochasticity such as Dropout improves the robustness and generalizability of deep neural networks. Here, we further demonstrate that always-on multiplicative stochasticity combined with simple threshold neurons are sufficient operations for deep neural networks. We call such models Neural Sampling Machi... | 1910.12316 | https://arxiv.org/abs/1910.12316v1 | https://arxiv.org/pdf/1910.12316v1.pdf | [] | [
"Weight Normalization",
"Dropout",
"Batch Normalization"
] | [] |
c45IPEAU_1 | https://paperswithcode.com/paper/beyond-node-embedding-a-direct-unsupervised | Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks | Network representation learning has traditionally been used to find lower dimensional vector representations of the nodes in a network. However, there are very important edge driven mining tasks of interest to the classical network analysis community, which have mostly been unexplored in the network embedding space. Fo... | 1912.05140 | https://arxiv.org/abs/1912.05140v1 | https://arxiv.org/pdf/1912.05140v1.pdf | [
"Link Prediction",
"Network Embedding",
"Representation Learning"
] | [
"LINE"
] | [] |
tfFDdXqlOa | https://paperswithcode.com/paper/machine-intelligence-for-outcome-predictions | Machine Intelligence for Outcome Predictions of Trauma Patients During Emergency Department Care | Trauma mortality results from a multitude of non-linear dependent risk factors including patient demographics, injury characteristics, medical care provided, and characteristics of medical facilities; yet traditional approach attempted to capture these relationships using rigid regression models. We hypothesized that a... | 2009.03873 | https://arxiv.org/abs/2009.03873v2 | https://arxiv.org/pdf/2009.03873v2.pdf | [
"Transfer Learning"
] | [] | [] |
ArNOEmUuFw | https://paperswithcode.com/paper/what-question-answering-can-learn-from-trivia | What Question Answering can Learn from Trivia Nerds | In addition to the traditional task of getting machines to answer questions, a major research question in question answering is to create interesting, challenging questions that can help systems learn how to answer questions and also reveal which systems are the best at answering questions. We argue that creating a que... | 1910.14464 | https://arxiv.org/abs/1910.14464v3 | https://arxiv.org/pdf/1910.14464v3.pdf | [
"Question Answering"
] | [] | [] |
JuTS5gdNAe | https://paperswithcode.com/paper/pretrain-to-finetune-adversarial-training-via | Pretrain-to-Finetune Adversarial Training via Sample-wise Randomized Smoothing | Developing certified models that can provably defense adversarial perturbations is important in machine learning security. Recently, randomized smoothing, combined with other techniques (Cohen et al., 2019; Salman et al., 2019), has been shown to be an effective method to certify models under $l_2$ perturbations. Exi... | null | https://openreview.net/forum?id=Te1aZ2myPIu | https://openreview.net/pdf?id=Te1aZ2myPIu | [] | [] | [] |
xLRonpmdTo | https://paperswithcode.com/paper/covid-19base-a-knowledgebase-to-explore | COVID-19Base: A knowledgebase to explore biomedical entities related to COVID-19 | We are presenting COVID-19Base, a knowledgebase highlighting the biomedical entities related to COVID-19 disease based on literature mining. To develop COVID-19Base, we mine the information from publicly available scientific literature and related public resources. We considered seven topic-specific dictionaries, inclu... | 2005.05954 | https://arxiv.org/abs/2005.05954v1 | https://arxiv.org/pdf/2005.05954v1.pdf | [
"Sentiment Analysis"
] | [] | [] |
Xm0XngH9Hr | https://paperswithcode.com/paper/novel-radiomic-feature-for-survival | Novel Radiomic Feature for Survival Prediction of Lung Cancer Patients using Low-Dose CBCT Images | Prediction of survivability in a patient for tumor progression is useful to estimate the effectiveness of a treatment protocol. In our work, we present a model to take into account the heterogeneous nature of a tumor to predict survival. The tumor heterogeneity is measured in terms of its mass by combining information ... | 2003.03537 | https://arxiv.org/abs/2003.03537v1 | https://arxiv.org/pdf/2003.03537v1.pdf | [
"Survival Analysis"
] | [] | [] |
mYA4KSYsQg | https://paperswithcode.com/paper/neural-networks-versus-logistic-regression | Neural networks versus Logistic regression for 30 days all-cause readmission prediction | Heart failure (HF) is one of the leading causes of hospital admissions in the
US. Readmission within 30 days after a HF hospitalization is both a recognized
indicator for disease progression and a source of considerable financial burden
to the healthcare system. Consequently, the identification of patients at risk
for ... | 1812.09549 | http://arxiv.org/abs/1812.09549v1 | http://arxiv.org/pdf/1812.09549v1.pdf | [
"Readmission Prediction"
] | [
"Logistic Regression"
] | [] |
PGs2njtXWk | https://paperswithcode.com/paper/successive-point-of-interest-recommendation | Successive Point-of-Interest Recommendation with Local Differential Privacy | A point-of-interest (POI) recommendation system plays an important role in location-based services (LBS) because it can help people to explore new locations and promote advertisers to launch ads to target users. Exiting POI recommendation methods need users' raw check-in data, which can raise location privacy breaches.... | 1908.09485 | https://arxiv.org/abs/1908.09485v1 | https://arxiv.org/pdf/1908.09485v1.pdf | [
"Recommendation Systems"
] | [] | [] |
yXIDM6swFu | https://paperswithcode.com/paper/metaphor-detection-using-ensembles-of | Metaphor Detection using Ensembles of Bidirectional Recurrent Neural Networks | In this paper we present our results from the Second Shared Task on Metaphor Detection, hosted by the Second Workshop on Figurative Language Processing. We use an ensemble of RNN models with bidirectional LSTMs and bidirectional attention mechanisms. Some of the models were trained on all parts of speech. Each of the o... | null | https://www.aclweb.org/anthology/2020.figlang-1.33/ | https://www.aclweb.org/anthology/2020.figlang-1.33 | [] | [] | [] |
tdpjCd9qAp | https://paperswithcode.com/paper/fast-saddle-point-algorithm-for-generalized | Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with the Ordered l1-Norm | In this paper we propose a primal-dual proximal extragradient algorithm to
solve the generalized Dantzig selector (GDS) estimation problem, based on a new
convex-concave saddle-point (SP) reformulation. Our new formulation makes it
possible to adopt recent developments in saddle-point optimization, to achieve
the optim... | 1511.05864 | http://arxiv.org/abs/1511.05864v3 | http://arxiv.org/pdf/1511.05864v3.pdf | [] | [
"ADMM"
] | [] |
Su3wrT-_MQ | https://paperswithcode.com/paper/lightweight-residual-network-for-the | Lightweight Residual Network for The Classification of Thyroid Nodules | Ultrasound is a useful technique for diagnosing thyroid nodules. Benign and malignant nodules that automatically discriminate in the ultrasound pictures can provide diagnostic recommendations or, improve diagnostic accuracy in the absence of specialists. The main issue here is how to collect suitable features for this ... | 1911.08303 | https://arxiv.org/abs/1911.08303v1 | https://arxiv.org/pdf/1911.08303v1.pdf | [] | [] | [] |
qg97JPkseR | https://paperswithcode.com/paper/a-comprehensive-analysis-of-information | A Comprehensive Analysis of Information Leakage in Deep Transfer Learning | Transfer learning is widely used for transferring knowledge from a source domain to the target domain where the labeled data is scarce. Recently, deep transfer learning has achieved remarkable progress in various applications. However, the source and target datasets usually belong to two different organizations in many... | 2009.01989 | https://arxiv.org/abs/2009.01989v1 | https://arxiv.org/pdf/2009.01989v1.pdf | [
"Transfer Learning"
] | [] | [] |
zVtmuFJQ5e | https://paperswithcode.com/paper/finding-statistically-significant-communities | Finding statistically significant communities in networks | Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units. Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multi-purpose techniques, able to handle different types... | 1012.2363 | https://arxiv.org/abs/1012.2363v2 | https://arxiv.org/pdf/1012.2363v2.pdf | [] | [] | [] |
2z9Up03Vp6 | https://paperswithcode.com/paper/when-compressive-learning-fails-blame-the | When compressive learning fails: blame the decoder or the sketch? | In compressive learning, a mixture model (a set of centroids or a Gaussian mixture) is learned from a sketch vector, that serves as a highly compressed representation of the dataset. This requires solving a non-convex optimization problem, hence in practice approximate heuristics (such as CLOMPR) are used. In this work... | 2009.08273 | https://arxiv.org/abs/2009.08273v1 | https://arxiv.org/pdf/2009.08273v1.pdf | [] | [] | [] |
SuljoLi9wP | https://paperswithcode.com/paper/back-to-rgb-3d-tracking-of-hands-and-hand | Back to RGB: 3D tracking of hands and hand-object interactions based on short-baseline stereo | We present a novel solution to the problem of 3D tracking of the articulated
motion of human hand(s), possibly in interaction with other objects. The vast
majority of contemporary relevant work capitalizes on depth information
provided by RGBD cameras. In this work, we show that accurate and efficient 3D
hand tracking ... | 1705.05301 | http://arxiv.org/abs/1705.05301v1 | http://arxiv.org/pdf/1705.05301v1.pdf | [
"3D Reconstruction"
] | [] | [] |
4av5kmMul7 | https://paperswithcode.com/paper/clipper-a-low-latency-online-prediction | Clipper: A Low-Latency Online Prediction Serving System | Machine learning is being deployed in a growing number of applications which
demand real-time, accurate, and robust predictions under heavy query load.
However, most machine learning frameworks and systems only address model
training and not deployment.
In this paper, we introduce Clipper, a general-purpose low-laten... | 1612.03079 | http://arxiv.org/abs/1612.03079v2 | http://arxiv.org/pdf/1612.03079v2.pdf | [
"Model Selection"
] | [] | [] |
zusAlGQ5mD | https://paperswithcode.com/paper/n-ode-transformer-a-depth-adaptive-variant-of | N-ODE Transformer: A Depth-Adaptive Variant of the Transformer Using Neural Ordinary Differential Equations | We use neural ordinary differential equations to formulate a variant of the Transformer that is depth-adaptive in the sense that an input-dependent number of time steps is taken by the ordinary differential equation solver. Our goal in proposing the N-ODE Transformer is to investigate whether its depth-adaptivity may a... | 2010.11358 | https://arxiv.org/abs/2010.11358v1 | https://arxiv.org/pdf/2010.11358v1.pdf | [
"Machine Translation"
] | [
"Residual Connection",
"Adam",
"Dense Connections",
"Softmax",
"Multi-Head Attention",
"Scaled Dot-Product Attention",
"Transformer"
] | [] |
vlE3zqEemS | https://paperswithcode.com/paper/rendu-base-image-avec-contraintes-sur-les | Rendu basé image avec contraintes sur les gradients | Multi-view image-based rendering consists in generating a novel view of a
scene from a set of source views. In general, this works by first doing a
coarse 3D reconstruction of the scene, and then using this reconstruction to
establish correspondences between source and target views, followed by blending
the warped view... | 1812.11339 | http://arxiv.org/abs/1812.11339v1 | http://arxiv.org/pdf/1812.11339v1.pdf | [
"3D Reconstruction"
] | [] | [] |
bTpVIHN0CW | https://paperswithcode.com/paper/collaborative-planning-for-mixed-autonomy | Collaborative Planning for Mixed-Autonomy Lane Merging | Driving is a social activity: drivers often indicate their intent to change
lanes via motion cues. We consider mixed-autonomy traffic where a Human-driven
Vehicle (HV) and an Autonomous Vehicle (AV) drive together. We propose a
planning framework where the degree to which the AV considers the other agent's
reward is co... | 1808.02550 | http://arxiv.org/abs/1808.02550v1 | http://arxiv.org/pdf/1808.02550v1.pdf | [
"Decision Making"
] | [] | [] |
1pH1X-MG14 | https://paperswithcode.com/paper/using-latinflexi-for-an-entropy-based | Using LatInfLexi for an Entropy-Based Assessment of Predictability in Latin Inflection | This paper presents LatInfLexi, a large inflected lexicon of Latin providing information on all the inflected wordforms of 3,348 verbs and 1,038 nouns. After a description of the structure of the resource and some data on its size, the procedure followed to obtain the lexicon from the database of the Lemlat 3.0 morphol... | null | https://www.aclweb.org/anthology/2020.lt4hala-1.6/ | https://www.aclweb.org/anthology/2020.lt4hala-1.6 | [] | [] | [] |
XMPzceZSse | https://paperswithcode.com/paper/a-simple-efficient-density-estimator-that | A simple efficient density estimator that enables fast systematic search | This paper introduces a simple and efficient density estimator that enables
fast systematic search. To show its advantage over commonly used kernel density
estimator, we apply it to outlying aspects mining. Outlying aspects mining
discovers feature subsets (or subspaces) that describe how a query stand out
from a given... | 1707.00783 | http://arxiv.org/abs/1707.00783v2 | http://arxiv.org/pdf/1707.00783v2.pdf | [
"Small Data Image Classification"
] | [] | [] |
pobKe792ce | https://paperswithcode.com/paper/on-the-reduction-of-variance-and | On the Reduction of Variance and Overestimation of Deep Q-Learning | The breakthrough of deep Q-Learning on different types of environments revolutionized the algorithmic design of Reinforcement Learning to introduce more stable and robust algorithms, to that end many extensions to deep Q-Learning algorithm have been proposed to reduce the variance of the target values and the overestim... | 1910.05983 | https://arxiv.org/abs/1910.05983v1 | https://arxiv.org/pdf/1910.05983v1.pdf | [
"Q-Learning"
] | [
"Q-Learning",
"Dropout"
] | [] |
v6oO-IrNiT | https://paperswithcode.com/paper/dual-subtitles-as-parallel-corpora | Dual Subtitles as Parallel Corpora | In this paper, we leverage the existence of dual subtitles as a source of parallel data. Dual subtitles present viewers with two languages simultaneously, and are generally aligned in the segment level, which removes the need to automatically perform this alignment. This is desirable as extracted parallel data does not... | null | https://www.aclweb.org/anthology/L14-1137/ | http://www.lrec-conf.org/proceedings/lrec2014/pdf/1199_Paper.pdf | [
"Machine Translation",
"Word Sense Disambiguation"
] | [] | [] |
MbhS2NW-ic | https://paperswithcode.com/paper/robust-physical-world-attacks-on-deep-1 | Robust Physical-World Attacks on Deep Learning Visual Classification | Recent studies show that the state-of-the-art deep neural networks (DNNs) are vulnerable to adversarial examples, resulting from small-magnitude perturbations added to the input. Given that that emerging physical systems are using DNNs in safety-critical situations, adversarial examples could mislead these systems and ... | null | http://openaccess.thecvf.com/content_cvpr_2018/html/Eykholt_Robust_Physical-World_Attacks_CVPR_2018_paper.html | http://openaccess.thecvf.com/content_cvpr_2018/papers/Eykholt_Robust_Physical-World_Attacks_CVPR_2018_paper.pdf | [] | [] | [] |
5zo1q4D1X_ | https://paperswithcode.com/paper/a-convolutional-approach-to-vertebrae | A Convolutional Approach to Vertebrae Detection and Labelling in Whole Spine MRI | We propose a novel convolutional method for the detection and identification of vertebrae in whole spine MRIs. This involves using a learnt vector field to group detected vertebrae corners together into individual vertebral bodies and convolutional image-to-image translation followed by beam search to label vertebral l... | 2007.02606 | https://arxiv.org/abs/2007.02606v3 | https://arxiv.org/pdf/2007.02606v3.pdf | [
"Image-to-Image Translation"
] | [] | [] |
Z_RDNRXXhj | https://paperswithcode.com/paper/if-dropout-limits-trainable-depth-does | If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks | Recent work in signal propagation theory has shown that dropout limits the depth to which information can propagate through a neural network. In this paper, we investigate the effect of initialisation on training speed and generalisation for ReLU networks within this depth limit. We ask the following research question:... | 1910.05725 | https://arxiv.org/abs/1910.05725v2 | https://arxiv.org/pdf/1910.05725v2.pdf | [] | [
"ReLU",
"Dropout"
] | [] |
g_DfPAB0o0 | https://paperswithcode.com/paper/inferring-analogous-attributes | Inferring Analogous Attributes | The appearance of an attribute can vary considerably from class to class (e.g., a "fluffy" dog vs. a "fluffy" towel), making standard class-independent attribute models break down. Yet, training object-specific models for each attribute can be impractical, and defeats the purpose of using attributes to bridge category ... | null | http://openaccess.thecvf.com/content_cvpr_2014/html/Chen_Inferring_Analogous_Attributes_2014_CVPR_paper.html | http://openaccess.thecvf.com/content_cvpr_2014/papers/Chen_Inferring_Analogous_Attributes_2014_CVPR_paper.pdf | [
"Transfer Learning"
] | [] | [] |
Kat6JqEnbE | https://paperswithcode.com/paper/rethinking-monocular-depth-estimation-with | Rethinking Monocular Depth Estimation with Adversarial Training | Monocular depth estimation is an extensively studied computer vision problem with a vast variety of applications. Deep learning-based methods have demonstrated promise for both supervised and unsupervised depth estimation from monocular images. Most existing approaches treat depth estimation as a regression problem wit... | 1808.07528 | https://arxiv.org/abs/1808.07528v3 | https://arxiv.org/pdf/1808.07528v3.pdf | [
"Depth Estimation",
"Monocular Depth Estimation"
] | [
"Concatenated Skip Connection",
"ReLU",
"Max Pooling",
"U-Net",
"Convolution",
"Spectral Normalization",
"GAN"
] | [] |
mTnyIdP805 | https://paperswithcode.com/paper/message-passing-for-probabilistic-models-on | Message passing for probabilistic models on networks with loops | In this paper, we extend a recently proposed framework for message passing on "loopy" networks to the solution of probabilistic models. We derive a self-consistent set of message passing equations that allow for fast computation of probability distributions in systems that contain short loops, potentially with high den... | 2009.12246 | https://arxiv.org/abs/2009.12246v1 | https://arxiv.org/pdf/2009.12246v1.pdf | [] | [] | [] |
UfkN1GsJ34 | https://paperswithcode.com/paper/extracting-weighted-language-lexicons-from | Extracting Weighted Language Lexicons from Wikipedia | Language models are used in applications as diverse as speech recognition, optical character recognition and information retrieval. They are used to predict word appearance, and to weight the importance of words in these applications. One basic element of language models is the list of words in a language. Another is t... | null | https://www.aclweb.org/anthology/L16-1217/ | https://www.aclweb.org/anthology/L16-1217 | [
"Information Retrieval",
"Language Modelling",
"Optical Character Recognition",
"Speech Recognition"
] | [] | [] |
BCHmuG2jRn | https://paperswithcode.com/paper/communication-computation-efficient-secure | Communication-Computation Efficient Secure Aggregation for Federated Learning | Federated learning has been spotlighted as a way to train neural network models using data distributed over multiple clients without a need to share private data. Unfortunately, however, it has been shown that data privacy could not be fully guaranteed as adversaries may be able to extract certain information on local ... | null | https://openreview.net/forum?id=0h9cYBqucS6 | https://openreview.net/pdf?id=0h9cYBqucS6 | [
"Federated Learning"
] | [] | [] |
1i-fCSHvrA | https://paperswithcode.com/paper/dirac-delta-regression-conditional-density | Dirac Delta Regression: Conditional Density Estimation with Clinical Trials | Personalized medicine seeks to identify the causal effect of treatment for a particular patient as opposed to a clinical population at large. Most investigators estimate such personalized treatment effects by regressing the outcome of a randomized clinical trial (RCT) on patient covariates. The realized value of the ou... | 1905.10330 | https://arxiv.org/abs/1905.10330v1 | https://arxiv.org/pdf/1905.10330v1.pdf | [
"Causal Inference",
"Density Estimation"
] | [] | [] |
LtAdUh4G51 | https://paperswithcode.com/paper/facial-aging-and-rejuvenation-by-conditional | Facial Aging and Rejuvenation by Conditional Multi-Adversarial Autoencoder with Ordinal Regression | Facial aging and facial rejuvenation analyze a given face photograph to
predict a future look or estimate a past look of the person. To achieve this,
it is critical to preserve human identity and the corresponding aging
progression and regression with high accuracy. However, existing methods cannot
simultaneously handl... | 1804.02740 | http://arxiv.org/abs/1804.02740v1 | http://arxiv.org/pdf/1804.02740v1.pdf | [
"Age Estimation"
] | [] | [] |
0Vh_3AhRlR | https://paperswithcode.com/paper/random-forest-regression-for-manifold-valued | Random Forest regression for manifold-valued responses | An increasing array of biomedical and computer vision applications requires
the predictive modeling of complex data, for example images and shapes. The
main challenge when predicting such objects lies in the fact that they do not
comply to the assumptions of Euclidean geometry. Rather, they occupy non-linear
spaces, a.... | 1701.08381 | http://arxiv.org/abs/1701.08381v2 | http://arxiv.org/pdf/1701.08381v2.pdf | [] | [] | [] |
totaq2jqu- | https://paperswithcode.com/paper/simulating-user-learning-in-authoritative | Simulating user learning in authoritative technology adoption: An agent based model for council-led smart meter deployment planning in the UK | How do technology users effectively transit from having zero knowledge about
a technology to making the best use of it after an authoritative technology
adoption? This post-adoption user learning has received little research
attention in technology management literature. In this paper we investigate
user learning in au... | 1607.05912 | http://arxiv.org/abs/1607.05912v1 | http://arxiv.org/pdf/1607.05912v1.pdf | [] | [] | [] |
rCZGhcm3lS | https://paperswithcode.com/paper/cross-corpus-data-augmentation-for-acoustic | Cross-Corpus Data Augmentation for Acoustic Addressee Detection | Acoustic addressee detection (AD) is a modern paralinguistic and dialogue challenge that especially arises in voice assistants. In the present study, we distinguish addressees in two settings (a conversation between several people and a spoken dialogue system, and a conversation between several adults and a child) and ... | null | https://www.aclweb.org/anthology/W19-5933/ | https://www.aclweb.org/anthology/W19-5933 | [
"Data Augmentation"
] | [
"Mixup"
] | [] |
m6qxxoVQ0k | https://paperswithcode.com/paper/self-adversarial-learning-with-comparative-1 | Self-Adversarial Learning with Comparative Discrimination for Text Generation | Conventional Generative Adversarial Networks (GANs) for text generation tend to have issues of reward sparsity and mode collapse that affect the quality and diversity of generated samples. To address the issues, we propose a novel self-adversarial learning (SAL) paradigm for improving GANs' performance in text generati... | 2001.11691 | https://arxiv.org/abs/2001.11691v2 | https://arxiv.org/pdf/2001.11691v2.pdf | [
"Text Generation"
] | [] | [] |
oYTu0_xuan | https://paperswithcode.com/paper/closed-loop-matters-dual-regression-networks | Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution | Deep neural networks have exhibited promising performance in image super-resolution (SR) by learning a nonlinear mapping function from low-resolution (LR) images to high-resolution (HR) images. However, there are two underlying limitations to existing SR methods. First, learning the mapping function from LR to HR image... | 2003.07018 | https://arxiv.org/abs/2003.07018v4 | https://arxiv.org/pdf/2003.07018v4.pdf | [
"Image Super-Resolution",
"Super Resolution",
"Super-Resolution"
] | [] | [] |
9-MU2AHd7V | https://paperswithcode.com/paper/metamta-metalearning-method-leveraging | MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low Resource Machine Translation | Manipulating training data leads to robust neural models for MT. | 1912.05467 | https://arxiv.org/abs/1912.05467v1 | https://arxiv.org/pdf/1912.05467v1.pdf | [
"Machine Translation"
] | [] | [] |
goWs6XkOXl | https://paperswithcode.com/paper/elicitation-complexity-of-statistical | Elicitation Complexity of Statistical Properties | A property, or statistical functional, is said to be elicitable if it minimizes expected loss for some loss function. The study of which properties are elicitable sheds light on the capabilities and limitations of point estimation and empirical risk minimization. While recent work asks which properties are elicitable, ... | 1506.07212 | https://arxiv.org/abs/1506.07212v3 | https://arxiv.org/pdf/1506.07212v3.pdf | [] | [] | [] |
ukjBCw48S- | https://paperswithcode.com/paper/why-so-gloomy-a-bayesian-explanation-of-human | Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task | How humans make repeated choices among options with imperfectly known reward outcomes is an important problem in psychology and neuroscience. This is often studied using multi-armed bandits, which is also frequently studied in machine learning. We present data from a human stationary bandit experiment, in which we vary... | null | http://papers.nips.cc/paper/7764-why-so-gloomy-a-bayesian-explanation-of-human-pessimism-bias-in-the-multi-armed-bandit-task | http://papers.nips.cc/paper/7764-why-so-gloomy-a-bayesian-explanation-of-human-pessimism-bias-in-the-multi-armed-bandit-task.pdf | [
"Multi-Armed Bandits"
] | [
"Softmax"
] | [] |
u9ewEjzoTN | https://paperswithcode.com/paper/analyze-and-development-system-with-multiple | Analyze and Development System with Multiple Biometric Identification | Cause of a rapid increase in technological development, increasing identity theft, consumer fraud, the threat to personal data is also increasing every day. Methods developed earlier to ensure personal the information from the thefts was not effective and safe. Biometrics were introduced when it was needed technology f... | 2004.04911 | https://arxiv.org/abs/2004.04911v1 | https://arxiv.org/pdf/2004.04911v1.pdf | [] | [] | [] |
YnjrQGDnfH | https://paperswithcode.com/paper/a-discriminative-framework-for-anomaly | A Discriminative Framework for Anomaly Detection in Large Videos | We address an anomaly detection setting in which training sequences are
unavailable and anomalies are scored independently of temporal ordering.
Current algorithms in anomaly detection are based on the classical density
estimation approach of learning high-dimensional models and finding
low-probability events. These al... | 1609.08938 | http://arxiv.org/abs/1609.08938v1 | http://arxiv.org/pdf/1609.08938v1.pdf | [
"Anomaly Detection",
"Density Estimation"
] | [] | [] |
e9xzlFs5zp | https://paperswithcode.com/paper/decamouflage-a-framework-to-detect-image | Decamouflage: A Framework to Detect Image-Scaling Attacks on Convolutional Neural Networks | As an essential processing step in computer vision applications, image resizing or scaling, more specifically downsampling, has to be applied before feeding a normally large image into a convolutional neural network (CNN) model because CNN models typically take small fixed-size images as inputs. However, image scaling ... | 2010.03735 | https://arxiv.org/abs/2010.03735v1 | https://arxiv.org/pdf/2010.03735v1.pdf | [] | [] | [] |
ddRaWXa4ls | https://paperswithcode.com/paper/deepdownscale-a-deep-learning-strategy-for | DeepDownscale: a Deep Learning Strategy for High-Resolution Weather Forecast | Running high-resolution physical models is computationally expensive and
essential for many disciplines. Agriculture, transportation, and energy are
sectors that depend on high-resolution weather models, which typically consume
many hours of large High Performance Computing (HPC) systems to deliver timely
results. Many... | 1808.05264 | http://arxiv.org/abs/1808.05264v1 | http://arxiv.org/pdf/1808.05264v1.pdf | [] | [] | [] |
s45bQ5bXHC | https://paperswithcode.com/paper/twowingos-a-two-wing-optimization-strategy | TwoWingOS: A Two-Wing Optimization Strategy for Evidential Claim Verification | Determining whether a given claim is supported by evidence is a fundamental
NLP problem that is best modeled as Textual Entailment. However, given a large
collection of text, finding evidence that could support or refute a given claim
is a challenge in itself, amplified by the fact that different evidence might
be need... | 1808.03465 | http://arxiv.org/abs/1808.03465v2 | http://arxiv.org/pdf/1808.03465v2.pdf | [
"Natural Language Inference"
] | [] | [] |
GNcq_05twd | https://paperswithcode.com/paper/theory-iiib-generalization-in-deep-networks | Theory IIIb: Generalization in Deep Networks | A main puzzle of deep neural networks (DNNs) revolves around the apparent
absence of "overfitting", defined in this paper as follows: the expected error
does not get worse when increasing the number of neurons or of iterations of
gradient descent. This is surprising because of the large capacity demonstrated
by DNNs to... | 1806.11379 | http://arxiv.org/abs/1806.11379v1 | http://arxiv.org/pdf/1806.11379v1.pdf | [] | [] | [] |
eiMYDX-VZQ | https://paperswithcode.com/paper/improved-local-search-for-graph-edit-distance | Improved local search for graph edit distance | The graph edit distance (GED) measures the dissimilarity between two graphs as the minimal cost of a sequence of elementary operations transforming one graph into another. This measure is fundamental in many areas such as structural pattern recognition or classification. However, exactly computing GED is NP-hard. Among... | 1907.02929 | https://arxiv.org/abs/1907.02929v2 | https://arxiv.org/pdf/1907.02929v2.pdf | [] | [] | [] |
proR34eljv | https://paperswithcode.com/paper/edge-based-blur-kernel-estimation-using | Edge-Based Blur Kernel Estimation Using Sparse Representation and Self-Similarity | Blind image deconvolution is the problem of recovering the latent image from
the only observed blurry image when the blur kernel is unknown. In this paper,
we propose an edge-based blur kernel estimation method for blind motion
deconvolution. In our previous work, we incorporate both sparse representation
and self-simi... | 1811.07161 | http://arxiv.org/abs/1811.07161v1 | http://arxiv.org/pdf/1811.07161v1.pdf | [
"Deblurring",
"Image Deconvolution"
] | [] | [] |
JN5XbPnm1A | https://paperswithcode.com/paper/sum-of-squares-lower-bounds-for-sparse-pca | Sum-of-Squares Lower Bounds for Sparse PCA | This paper establishes a statistical versus computational trade-off for
solving a basic high-dimensional machine learning problem via a basic convex
relaxation method. Specifically, we consider the {\em Sparse Principal
Component Analysis} (Sparse PCA) problem, and the family of {\em
Sum-of-Squares} (SoS, aka Lasserre/... | 1507.06370 | http://arxiv.org/abs/1507.06370v2 | http://arxiv.org/pdf/1507.06370v2.pdf | [] | [] | [] |
qOhtF7WvRX | https://paperswithcode.com/paper/meteor-20-adopt-syntactic-level-paraphrase | Meteor++ 2.0: Adopt Syntactic Level Paraphrase Knowledge into Machine Translation Evaluation | This paper describes Meteor++ 2.0, our submission to the WMT19 Metric Shared Task. The well known Meteor metric improves machine translation evaluation by introducing paraphrase knowledge. However, it only focuses on the lexical level and utilizes consecutive n-grams paraphrases. In this work, we take into consideratio... | null | https://www.aclweb.org/anthology/W19-5357/ | https://www.aclweb.org/anthology/W19-5357 | [
"Machine Translation"
] | [] | [] |
p_joItUqH4 | https://paperswithcode.com/paper/exact-symbolic-inference-in-probabilistic | Exact Symbolic Inference in Probabilistic Programs via Sum-Product Representations | We present the Sum-Product Probabilistic Language (SPPL), a new system that automatically delivers exact solutions to a broad range of probabilistic inference queries. SPPL symbolically represents the full distribution on execution traces specified by a probabilistic program using a generalization of sum-product networ... | 2010.03485 | https://arxiv.org/abs/2010.03485v1 | https://arxiv.org/pdf/2010.03485v1.pdf | [
"fairness"
] | [] | [] |
Md6DdlhwhP | https://paperswithcode.com/paper/multi-observation-elicitation | Multi-Observation Elicitation | We study loss functions that measure the accuracy of a prediction based on
multiple data points simultaneously. To our knowledge, such loss functions have
not been studied before in the area of property elicitation or in machine
learning more broadly. As compared to traditional loss functions that take only
a single da... | 1706.01394 | http://arxiv.org/abs/1706.01394v1 | http://arxiv.org/pdf/1706.01394v1.pdf | [] | [] | [] |
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