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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8,101 to 8,160 of 9,699

Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study
Aditya Siddhant, Zachary C. Lipton
cs.CLcs.LGstat.MLarXiv:1808.05697v32018
Reinforcement Learning for Combinatorial Optimization: A Survey
Nina Mazyavkina, Sergey Sviridov, Sergei Ivanov +1
cs.LGmath.COmath.OCarXiv:2003.03600v32020
Density-Reweighted Entropic Optimal Transport: Decoupling Geometry from Sampling Density
Keyi Li, Yuval Kluger, Boris Landa
stat.MLcs.LGstat.AParXiv:2608.16506v12026
Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing
Shengchao Liu, Weili Nie, Chengpeng Wang +6
cs.LGcs.CLq-bio.QMarXiv:2212.10789v32022
Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter Decomposition
Dan Braun, Lucius Bushnaq, Stefan Heimersheim +2
cs.LGstat.MLarXiv:2501.14926v42025
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
Raef Bassily, Vitaly Feldman, Cristóbal Guzmán +1
cs.LGmath.OCstat.MLarXiv:2006.06914v12020
Supervised Topic Models
David M. Blei, Jon D. McAuliffe
stat.MLarXiv:1003.0783v12010
Broadly Applicable Approximate MCMC for Switching Stochastic Differential Equations Using Uniformization and Time-Conditioned Factorized Neural Likelihood Estimation
Shion Hosoda, Michiaki Hamada
stat.MLcs.LGarXiv:2610.10194v12026
NVAE: A Deep Hierarchical Variational Autoencoder
Arash Vahdat, Jan Kautz
stat.MLcs.CVcs.LGarXiv:2007.03898v32020
Anchored Extra-Proximal Methods: Optimal Higher-Order Methods for Monotone Inclusion Problems
Ruichen Jiang, TaeHo Yoon
math.OCcs.LGstat.MLarXiv:2609.30212v12026
COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios
Rodolfo M. Pereira, Diego Bertolini, Lucas O. Teixeira +2
cs.LGstat.MLarXiv:2004.05835v32020
Complementary-Label Learning for Arbitrary Losses and Models
Takashi Ishida, Gang Niu, Aditya Krishna Menon +1
stat.MLcs.LGarXiv:1810.04327v42018
Assessing Generalization of SGD via Disagreement
Yiding Jiang, Vaishnavh Nagarajan, Christina Baek +1
cs.LGcs.AIstat.MLarXiv:2106.13799v22021
Differentially Private Contextual Linear Bandits
Roshan Shariff, Or Sheffet
cs.LGstat.MLarXiv:1810.00068v12018
Quantum machine learning: a classical perspective
Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo +4
quant-phcs.LGstat.MLarXiv:1707.08561v32017
Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani +2
cs.LGcs.CRcs.CVarXiv:2101.04898v22021
Learning under Concept Drift: A Review
Jie Lu, Anjin Liu, Fan Dong +3
cs.LGstat.MLarXiv:2004.05785v12020
Defending against Backdoors in Federated Learning with Robust Learning Rate
Mustafa Safa Ozdayi, Murat Kantarcioglu, Yulia R. Gel
cs.LGcs.CRstat.MLarXiv:2007.03767v42020
Continual Learning and Catastrophic Forgetting
Gido M. van de Ven, Nicholas Soures, Dhireesha Kudithipudi
cs.LGcs.AIcs.CVarXiv:2403.05175v12024
Thompson Sampling for Contextual Bandits with Linear Payoffs
Shipra Agrawal, Navin Goyal
cs.LGcs.DSstat.MLarXiv:1209.3352v42012
Federated Graph Classification over Non-IID Graphs
Han Xie, Jing Ma, Li Xiong +1
cs.LGcs.AIcs.DCarXiv:2106.13423v52021
REPAIR: REnormalizing Permuted Activations for Interpolation Repair
Keller Jordan, Hanie Sedghi, Olga Saukh +2
cs.LGcs.AIcs.CVarXiv:2211.08403v32022
Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching
Yunsheng Bai, Hao Ding, Yizhou Sun +1
cs.LGstat.MLarXiv:1809.04440v22018
CEM-RL: Combining evolutionary and gradient-based methods for policy search
Aloïs Pourchot, Olivier Sigaud
cs.LGcs.NEstat.MLarXiv:1810.01222v32018
Parsimonious module inference in large networks
Tiago P. Peixoto
physics.data-anphysics.soc-phstat.MLarXiv:1212.4794v42012
A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity
Hoda Heidari, Michele Loi, Krishna P. Gummadi +1
cs.LGecon.THstat.MLarXiv:1809.03400v22018
VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification
Zhibin Lu, Pan Du, Jian-Yun Nie
cs.CLcs.LGstat.MLarXiv:2004.05707v12020
DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN
Swee Kiat Lim, Yi Loo, Ngoc-Trung Tran +3
cs.LGstat.MLarXiv:1808.07632v22018
Omega-Regular Objectives in Model-Free Reinforcement Learning
Ernst Moritz Hahn, Mateo Perez, Sven Schewe +3
cs.LOcs.LGstat.MLarXiv:1810.00950v12018
High Accuracy and High Fidelity Extraction of Neural Networks
Matthew Jagielski, Nicholas Carlini, David Berthelot +2
cs.LGcs.CRstat.MLarXiv:1909.01838v22019
Deep Anomaly Detection with Deviation Networks
Guansong Pang, Chunhua Shen, Anton van den Hengel
cs.LGstat.MLarXiv:1911.08623v12019
A Survey on Large-scale Machine Learning
Meng Wang, Weijie Fu, Xiangnan He +2
cs.LGstat.MLarXiv:2008.03911v12020
StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion
Takuhiro Kaneko, Hirokazu Kameoka, Kou Tanaka +1
cs.SDcs.LGeess.ASarXiv:1907.12279v22019
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes
Ohad Shamir, Tong Zhang
cs.LGmath.OCstat.MLarXiv:1212.1824v22012
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker, Andriy Mnih, Chris J. Maddison +2
cs.LGstat.MLarXiv:1703.07370v42017
Probability flow ODEs in score-based and reflected diffusion models
Rama CONT
stat.MLcs.LGmath.PRarXiv:2610.03846v12026
Lasso Screening Rules via Dual Polytope Projection
Jie Wang, Peter Wonka, Jieping Ye
cs.LGstat.MLarXiv:1211.3966v32012
Targeted Active Learning for Preference-Based Treatment Effects on Multivariate Outcomes
Lola Giordani, Mathieu Even, Chloé Geoffroy +3
stat.MLcs.LGstat.MEarXiv:2610.03824v12026
The Convergence of Sparsified Gradient Methods
Dan Alistarh, Torsten Hoefler, Mikael Johansson +3
cs.LGcs.DCstat.MLarXiv:1809.10505v12018
Practical Obstacles to Deploying Active Learning
David Lowell, Zachary C. Lipton, Byron C. Wallace
cs.LGstat.MLarXiv:1807.04801v32018
Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing
Chen Liang, Mohammad Norouzi, Jonathan Berant +2
cs.LGcs.AIcs.CLarXiv:1807.02322v52018
Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks
Yuhang Li, Xin Dong, Wei Wang
cs.LGstat.MLarXiv:1909.13144v22019
Convolutional Conditional Neural Processes
Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong +3
stat.MLcs.LGarXiv:1910.13556v52019
Learning One-hidden-layer ReLU Networks via Gradient Descent
Xiao Zhang, Yaodong Yu, Lingxiao Wang +1
stat.MLcs.LGarXiv:1806.07808v12018
Learning Individually Inferred Communication for Multi-Agent Cooperation
Ziluo Ding, Tiejun Huang, Zongqing Lu
cs.LGcs.MAstat.MLarXiv:2006.06455v22020
Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models
Garrett Bernstein, Ryan McKenna, Tao Sun +3
cs.LGcs.CRstat.MLarXiv:1706.04646v12017
Penalizing side effects using stepwise relative reachability
Victoria Krakovna, Laurent Orseau, Ramana Kumar +2
cs.LGcs.AIstat.MLarXiv:1806.01186v22018
Private PAC learning implies finite Littlestone dimension
Noga Alon, Roi Livni, Maryanthe Malliaris +1
cs.LGcs.AIcs.CRarXiv:1806.00949v32018
m-Set Adversarial Bandits with Winner Feedback
Nicolò Cesa-Bianchi, Matteo Papini
cs.LGstat.MLarXiv:2610.10128v12026
Bayesian approach to model-based extrapolation of nuclear observables
Léo Neufcourt, Yuchen Cao, Witold Nazarewicz +1
nucl-thstat.MLarXiv:1806.00552v32018
DeepMoD: Deep learning for Model Discovery in noisy data
Gert-Jan Both, Subham Choudhury, Pierre Sens +1
physics.comp-phq-bio.QMstat.MLarXiv:1904.09406v32019
dna2vec: Consistent vector representations of variable-length k-mers
Patrick Ng
q-bio.QMcs.CLcs.LGarXiv:1701.06279v12017
Fast Policy Learning through Imitation and Reinforcement
Ching-An Cheng, Xinyan Yan, Nolan Wagener +1
cs.LGstat.MLarXiv:1805.10413v12018
Summaries:한국어
Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning
Huy Phan, Oliver Y. Chén, Philipp Koch +4
cs.LGeess.SPstat.MLarXiv:1907.13177v32019
ViWi: A Deep Learning Dataset Framework for Vision-Aided Wireless Communications
Muhammad Alrabeiah, Andrew Hredzak, Zhenhao Liu +1
cs.LGcs.ITeess.SParXiv:1911.06257v22019
The Feature Importance Ranking Measure
Alexander Zien, Nicole Kraemer, Soeren Sonnenburg +1
stat.MLarXiv:0906.4258v12009
Causal Inference for Time series Analysis: Problems, Methods and Evaluation
Raha Moraffah, Paras Sheth, Mansooreh Karami +5
cs.LGstat.MLarXiv:2102.05829v12021
Edge Contraction Pooling for Graph Neural Networks
Frederik Diehl
cs.LGstat.MLarXiv:1905.10990v12019
Off-grid Direction of Arrival Estimation Using Sparse Bayesian Inference
Zai Yang, Lihua Xie, Cishen Zhang
stat.APcs.ITstat.MLarXiv:1108.5838v42011
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks
Difan Zou, Yuan Cao, Dongruo Zhou +1
cs.LGcs.AImath.OCarXiv:1811.08888v32018

Machine Learning (stat)

Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study

Reinforcement Learning for Combinatorial Optimization: A Survey

Density-Reweighted Entropic Optimal Transport: Decoupling Geometry from Sampling Density

Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing

Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter Decomposition

Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses

Supervised Topic Models

Broadly Applicable Approximate MCMC for Switching Stochastic Differential Equations Using Uniformization and Time-Conditioned Factorized Neural Likelihood Estimation

NVAE: A Deep Hierarchical Variational Autoencoder

Anchored Extra-Proximal Methods: Optimal Higher-Order Methods for Monotone Inclusion Problems

COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios

Complementary-Label Learning for Arbitrary Losses and Models

Assessing Generalization of SGD via Disagreement

Differentially Private Contextual Linear Bandits

Quantum machine learning: a classical perspective

Unlearnable Examples: Making Personal Data Unexploitable

Learning under Concept Drift: A Review

Defending against Backdoors in Federated Learning with Robust Learning Rate

Continual Learning and Catastrophic Forgetting

Thompson Sampling for Contextual Bandits with Linear Payoffs

Federated Graph Classification over Non-IID Graphs

REPAIR: REnormalizing Permuted Activations for Interpolation Repair

Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching

CEM-RL: Combining evolutionary and gradient-based methods for policy search

Parsimonious module inference in large networks

A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity

VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification

DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN

Omega-Regular Objectives in Model-Free Reinforcement Learning

High Accuracy and High Fidelity Extraction of Neural Networks

Deep Anomaly Detection with Deviation Networks

A Survey on Large-scale Machine Learning

StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion

Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes

REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models

Probability flow ODEs in score-based and reflected diffusion models

Lasso Screening Rules via Dual Polytope Projection

Targeted Active Learning for Preference-Based Treatment Effects on Multivariate Outcomes

The Convergence of Sparsified Gradient Methods

Practical Obstacles to Deploying Active Learning

Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing

Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Convolutional Conditional Neural Processes

Learning One-hidden-layer ReLU Networks via Gradient Descent

Learning Individually Inferred Communication for Multi-Agent Cooperation

Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models

Penalizing side effects using stepwise relative reachability

Private PAC learning implies finite Littlestone dimension

m-Set Adversarial Bandits with Winner Feedback

Bayesian approach to model-based extrapolation of nuclear observables

DeepMoD: Deep learning for Model Discovery in noisy data

dna2vec: Consistent vector representations of variable-length k-mers

Fast Policy Learning through Imitation and Reinforcement

Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning

ViWi: A Deep Learning Dataset Framework for Vision-Aided Wireless Communications

The Feature Importance Ranking Measure

Causal Inference for Time series Analysis: Problems, Methods and Evaluation

Edge Contraction Pooling for Graph Neural Networks

Off-grid Direction of Arrival Estimation Using Sparse Bayesian Inference

Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks