Machine Learning (stat)

Papers filed under stat.ML on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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2,761 to 2,820 of 6,792

Deep Reinforcement Learning for Imbalanced Classification
Enlu Lin, Qiong Chen, Xiaoming Qi
cs.LGcs.AIstat.MLarXiv:1901.01379v12019
FedSplit: An algorithmic framework for fast federated optimization
Reese Pathak, Martin J. Wainwright
cs.LGmath.OCstat.MLarXiv:2005.05238v12020
Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL
Anusha Nagabandi, Chelsea Finn, Sergey Levine
cs.LGcs.AIcs.ROarXiv:1812.07671v22018
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
Ryan L. Murphy, Balasubramaniam Srinivasan, Vinayak Rao +1
cs.LGstat.MLarXiv:1811.01900v32018
Harmless interpolation of noisy data in regression
Vidya Muthukumar, Kailas Vodrahalli, Vignesh Subramanian +1
cs.LGstat.MLarXiv:1903.09139v22019
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits
Mikołaj Sacha, Mikołaj Błaż, Piotr Byrski +5
cs.LGphysics.chem-phstat.MLarXiv:2006.15426v22020
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes
Nathan Kallus, Masatoshi Uehara
cs.LGcs.AIstat.MLarXiv:1908.08526v32019
Capacity and Trainability in Recurrent Neural Networks
Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
stat.MLcs.AIcs.LGarXiv:1611.09913v32016
Generative and Discriminative Text Classification with Recurrent Neural Networks
Dani Yogatama, Chris Dyer, Wang Ling +1
stat.MLcs.CLcs.LGarXiv:1703.01898v22017
Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition
Dimitrios Kollias, Stefanos Zafeiriou
cs.CVcs.AIcs.LGarXiv:1811.07770v22018
A General Approach to Adding Differential Privacy to Iterative Training Procedures
H. Brendan McMahan, Galen Andrew, Ulfar Erlingsson +4
cs.LGstat.MLarXiv:1812.06210v22018
EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback
Peter Richtárik, Igor Sokolov, Ilyas Fatkhullin
cs.LGmath.OCstat.MLarXiv:2106.05203v12021
Adversarial AutoAugment
Xinyu Zhang, Qiang Wang, Jian Zhang +1
cs.CVcs.LGstat.MLarXiv:1912.11188v12019
Hierarchical Graph Pooling with Structure Learning
Zhen Zhang, Jiajun Bu, Martin Ester +4
cs.LGstat.MLarXiv:1911.05954v32019
DROCC: Deep Robust One-Class Classification
Sachin Goyal, Aditi Raghunathan, Moksh Jain +2
cs.LGstat.MLarXiv:2002.12718v22020
TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification
Ahmed Shifaz, Charlotte Pelletier, Francois Petitjean +1
cs.LGstat.MLarXiv:1906.10329v22019
Convergence for score-based generative modeling with polynomial complexity
Holden Lee, Jianfeng Lu, Yixin Tan
cs.LGmath.PRmath.STarXiv:2206.06227v22022
Graph Prototypical Networks for Few-shot Learning on Attributed Networks
Kaize Ding, Jianling Wang, Jundong Li +3
cs.LGcs.SIstat.MLarXiv:2006.12739v32020
Learning Parameterized Skills
Bruno Da Silva, George Konidaris, Andrew Barto
cs.LGstat.MLarXiv:1206.6398v22012
Deep Learning of Part-based Representation of Data Using Sparse Autoencoders with Nonnegativity Constraints
Ehsan Hosseini-Asl, Jacek M. Zurada, Olfa Nasraoui
cs.LGstat.MLarXiv:1601.02733v12016
FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning
Swanand Kadhe, Nived Rajaraman, O. Ozan Koyluoglu +1
cs.CRcs.ITcs.LGarXiv:2009.11248v12020
Node-Based Learning of Multiple Gaussian Graphical Models
Karthik Mohan, Palma London, Maryam Fazel +2
stat.MLcs.LGmath.OCarXiv:1303.5145v42013
Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing
Jingyi Wang, Guoliang Dong, Jun Sun +2
cs.LGcs.SEstat.MLarXiv:1812.05793v22018
Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization
Constantinos Daskalakis, Ioannis Panageas
math.OCcs.GTstat.MLarXiv:1807.04252v52018
Posterior Tempering Explains Variance Inflation in Linear and Generalized Linear Thompson Sampling
Prateek Jaiswal, Debdeep Pati, Anirban Bhattacharya +1
stat.MLcs.ITcs.LGarXiv:2609.01999v12026
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Yingzhen Li, Yarin Gal
cs.LGstat.MLarXiv:1703.02914v12017
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?
Simon S. Du, Sham M. Kakade, Ruosong Wang +1
cs.LGcs.AImath.OCarXiv:1910.03016v42019
The Uncertainty Bellman Equation and Exploration
Brendan O'Donoghue, Ian Osband, Remi Munos +1
cs.AIcs.LGmath.OCarXiv:1709.05380v42017
Exponential concentration in quantum kernel methods
Supanut Thanasilp, Samson Wang, M. Cerezo +1
quant-phcs.LGstat.MLarXiv:2208.11060v22022
Convergence of Langevin MCMC in KL-divergence
Xiang Cheng, Peter Bartlett
stat.MLarXiv:1705.09048v22017
Convolutional Conditional Neural Processes
Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong +3
stat.MLcs.LGarXiv:1910.13556v52019
Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis
Thomas George, César Laurent, Xavier Bouthillier +2
cs.LGstat.MLarXiv:1806.03884v22018
Bilinear Classes: A Structural Framework for Provable Generalization in RL
Simon S. Du, Sham M. Kakade, Jason D. Lee +4
cs.LGcs.AImath.OCarXiv:2103.10897v32021
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms
Hussein Hazimeh, Rahul Mazumder
stat.COmath.OCstat.MLarXiv:1803.01454v32018
Large Associative Memory Problem in Neurobiology and Machine Learning
Dmitry Krotov, John Hopfield
q-bio.NCcond-mat.dis-nncs.CLarXiv:2008.06996v32020
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy
T. Tony Cai, Yichen Wang, Linjun Zhang
stat.MLcs.CRcs.DSarXiv:1902.04495v52019
Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds
Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst +1
cs.LGcs.CVcs.SIarXiv:1303.2221v12013
What Would it Cost to End Extreme Poverty?
Roshni Sahoo, Joshua Blumenstock, Paul Niehaus +2
econ.GNstat.MLarXiv:2609.02013v12026
PAC-Bayesian Theory Meets Bayesian Inference
Pascal Germain, Francis Bach, Alexandre Lacoste +1
stat.MLcs.LGarXiv:1605.08636v42016
Stochastic Variance-Reduced Policy Gradient
Matteo Papini, Damiano Binaghi, Giuseppe Canonaco +2
cs.LGstat.MLarXiv:1806.05618v12018
Learning from Complementary Labels
Takashi Ishida, Gang Niu, Weihua Hu +1
stat.MLcs.LGarXiv:1705.07541v22017
A Deep Latent Variable Framework for Jointly Modeling Missingness, Measurement Error, and Heterogeneity
Yasin Khadem Charvadeh, Grace Y. Yi, Mithat Gönen +1
stat.MLcs.LGarXiv:2608.30040v12026
How is Machine Learning Useful for Macroeconomic Forecasting?
Philippe Goulet Coulombe, Maxime Leroux, Dalibor Stevanovic +1
econ.EMstat.APstat.MLarXiv:2008.12477v12020
The BOSARIS Toolkit: Theory, Algorithms and Code for Surviving the New DCF
Niko Brümmer, Edward de Villiers
stat.APcs.LGstat.MLarXiv:1304.2865v12013
Stream Graphs and Link Streams for the Modeling of Interactions over Time
Matthieu Latapy, Tiphaine Viard, Clémence Magnien
cs.SIcs.DMcs.DSarXiv:1710.04073v12017
Sanity Checks for Saliency Metrics
Richard Tomsett, Dan Harborne, Supriyo Chakraborty +2
cs.LGcs.CVeess.IVarXiv:1912.01451v12019
RADNET: Radiologist Level Accuracy using Deep Learning for HEMORRHAGE detection in CT Scans
Monika Grewal, Muktabh Mayank Srivastava, Pulkit Kumar +1
cs.CVstat.MLarXiv:1710.04934v22017
The Social Cost of Strategic Classification
Smitha Milli, John Miller, Anca D. Dragan +1
cs.LGstat.MLarXiv:1808.08460v22018
Uncertainty-guided Continual Learning with Bayesian Neural Networks
Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell +1
cs.LGcs.AIcs.CVarXiv:1906.02425v22019
Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing
Jill-Jênn Vie, Hisashi Kashima
cs.IRcs.AIcs.LGarXiv:1811.03388v22018
Predicting What You Already Know Helps: Provable Self-Supervised Learning
Jason D. Lee, Qi Lei, Nikunj Saunshi +1
cs.LGstat.MLarXiv:2008.01064v22020
WideDTA: prediction of drug-target binding affinity
Hakime Öztürk, Elif Ozkirimli, Arzucan Özgür
q-bio.QMcs.LGstat.MLarXiv:1902.04166v12019
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits
Julian Zimmert, Yevgeny Seldin
cs.LGstat.MLarXiv:1807.07623v62018
Exploration-Exploitation in Constrained MDPs
Yonathan Efroni, Shie Mannor, Matteo Pirotta
cs.LGstat.MLarXiv:2003.02189v12020
Sockeye: A Toolkit for Neural Machine Translation
Felix Hieber, Tobias Domhan, Michael Denkowski +4
cs.CLcs.LGstat.MLarXiv:1712.05690v22017
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
Emile Mathieu, Charline Le Lan, Chris J. Maddison +2
stat.MLcs.LGarXiv:1901.06033v32019
Hypernetwork Knowledge Graph Embeddings
Ivana Balažević, Carl Allen, Timothy M. Hospedales
cs.LGstat.MLarXiv:1808.07018v52018
The Randomized Dependence Coefficient
David Lopez-Paz, Philipp Hennig, Bernhard Schölkopf
stat.MLarXiv:1304.7717v22013
Explore no more: Improved high-probability regret bounds for non-stochastic bandits
Gergely Neu
cs.LGstat.MLarXiv:1506.03271v32015
Simple, Robust and Optimal Ranking from Pairwise Comparisons
Nihar B. Shah, Martin J. Wainwright
cs.LGcs.AIcs.ITarXiv:1512.08949v22015

Machine Learning (stat)

Deep Reinforcement Learning for Imbalanced Classification

FedSplit: An algorithmic framework for fast federated optimization

Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL

Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs

Harmless interpolation of noisy data in regression

Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits

Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes

Capacity and Trainability in Recurrent Neural Networks

Generative and Discriminative Text Classification with Recurrent Neural Networks

Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition

A General Approach to Adding Differential Privacy to Iterative Training Procedures

EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback

Adversarial AutoAugment

Hierarchical Graph Pooling with Structure Learning

DROCC: Deep Robust One-Class Classification

TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification

Convergence for score-based generative modeling with polynomial complexity

Graph Prototypical Networks for Few-shot Learning on Attributed Networks

Learning Parameterized Skills

Deep Learning of Part-based Representation of Data Using Sparse Autoencoders with Nonnegativity Constraints

FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning

Node-Based Learning of Multiple Gaussian Graphical Models

Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing

Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization

Posterior Tempering Explains Variance Inflation in Linear and Generalized Linear Thompson Sampling

Dropout Inference in Bayesian Neural Networks with Alpha-divergences

Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?

The Uncertainty Bellman Equation and Exploration

Exponential concentration in quantum kernel methods

Convergence of Langevin MCMC in KL-divergence

Convolutional Conditional Neural Processes

Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis

Bilinear Classes: A Structural Framework for Provable Generalization in RL

Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms

Large Associative Memory Problem in Neurobiology and Machine Learning

The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy

Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds

What Would it Cost to End Extreme Poverty?

PAC-Bayesian Theory Meets Bayesian Inference

Stochastic Variance-Reduced Policy Gradient

Learning from Complementary Labels

A Deep Latent Variable Framework for Jointly Modeling Missingness, Measurement Error, and Heterogeneity

How is Machine Learning Useful for Macroeconomic Forecasting?

The BOSARIS Toolkit: Theory, Algorithms and Code for Surviving the New DCF

Stream Graphs and Link Streams for the Modeling of Interactions over Time

Sanity Checks for Saliency Metrics

RADNET: Radiologist Level Accuracy using Deep Learning for HEMORRHAGE detection in CT Scans

The Social Cost of Strategic Classification

Uncertainty-guided Continual Learning with Bayesian Neural Networks

Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing

Predicting What You Already Know Helps: Provable Self-Supervised Learning

WideDTA: prediction of drug-target binding affinity

Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits

Exploration-Exploitation in Constrained MDPs

Sockeye: A Toolkit for Neural Machine Translation

Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders

Hypernetwork Knowledge Graph Embeddings

The Randomized Dependence Coefficient

Explore no more: Improved high-probability regret bounds for non-stochastic bandits

Simple, Robust and Optimal Ranking from Pairwise Comparisons