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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7,261 to 7,320 of 9,715

Batch Active Learning Using Determinantal Point Processes
Erdem Bıyık, Kenneth Wang, Nima Anari +1
cs.LGstat.MLarXiv:1906.07975v12019
Measuring the Algorithmic Efficiency of Neural Networks
Danny Hernandez, Tom B. Brown
cs.LGcs.CVstat.MLarXiv:2005.04305v12020
Heterogeneous domain adaptation: An unsupervised approach
Feng Liu, Guanquan Zhang, Jie Lu
cs.LGstat.MLarXiv:1701.02511v52017
Scaling provable adversarial defenses
Eric Wong, Frank R. Schmidt, Jan Hendrik Metzen +1
cs.LGcs.AImath.OCarXiv:1805.12514v22018
Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment
Audrey Huang, Adam Block, Qinghua Liu +3
cs.AIcs.LGstat.MLarXiv:2503.21878v22025
LAIR-Net: Leaky Alignment-Impulse Residual Networks for Tabular Regression
Rahul Goswami, Aryan Bhambu, Bittu Karmakar
stat.MLcs.LGarXiv:2610.11538v12026
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
Junyu Zhang, Alec Koppel, Amrit Singh Bedi +2
cs.LGstat.MLarXiv:2007.02151v12020
In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction
Caroline Wang, Bin Han, Bhrij Patel +1
stat.MLcs.LGstat.AParXiv:2005.04176v32020
End-to-End Robotic Reinforcement Learning without Reward Engineering
Avi Singh, Larry Yang, Kristian Hartikainen +2
cs.LGcs.CVcs.ROarXiv:1904.07854v22019
Adversarially Learned Inference
Vincent Dumoulin, Ishmael Belghazi, Ben Poole +4
stat.MLcs.LGarXiv:1606.00704v32016
On the Robustness of the Backdoor-based Watermarking in Deep Neural Networks
Masoumeh Shafieinejad, Jiaqi Wang, Nils Lukas +2
cs.LGcs.CRstat.MLarXiv:1906.07745v22019
Meta-GNN: On Few-shot Node Classification in Graph Meta-learning
Fan Zhou, Chengtai Cao, Kunpeng Zhang +3
cs.LGstat.MLarXiv:1905.09718v12019
To understand deep learning we need to understand kernel learning
Mikhail Belkin, Siyuan Ma, Soumik Mandal
stat.MLcs.LGarXiv:1802.01396v32018
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
Maurice Weiler, Mario Geiger, Max Welling +2
cs.LGstat.MLarXiv:1807.02547v22018
GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference
Ali Hadi Zadeh, Isak Edo, Omar Mohamed Awad +1
cs.LGcs.ARstat.MLarXiv:2005.03842v22020
Soft Threshold Weight Reparameterization for Learnable Sparsity
Aditya Kusupati, Vivek Ramanujan, Raghav Somani +4
cs.LGcs.CVstat.MLarXiv:2002.03231v92020
Federated Asymptotics: a model to compare federated learning algorithms
Gary Cheng, Karan Chadha, John Duchi
cs.LGcs.DCmath.OCarXiv:2108.07313v32021
Cautious Weight Decay
Lizhang Chen, Jonathan Li, Kaizhao Liang +6
cs.LGmath.OCstat.MLarXiv:2510.12402v22025
Multi-Task Learning with Deep Neural Networks: A Survey
Michael Crawshaw
cs.LGcs.CVstat.MLarXiv:2009.09796v12020
From Bandits to Experts: On the Value of Side-Observations
Shie Mannor, Ohad Shamir
cs.LGstat.MLarXiv:1106.2436v32011
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing
Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar +1
cs.LGcs.AIcs.CRarXiv:2002.03018v42020
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling
Jianyu Wang, Anit Kumar Sahu, Zhouyi Yang +2
cs.LGeess.SYmath.OCarXiv:1905.09435v32019
High-accuracy sampling for diffusion models and log-concave distributions
Fan Chen, Sinho Chewi, Constantinos Daskalakis +1
cs.LGmath.STstat.MLarXiv:2602.01338v22026
Tensor Logic: The Language of AI
Pedro Domingos
cs.AIcs.LGcs.NEarXiv:2510.12269v32025
Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks
Behnam Neyshabur, Zhiyuan Li, Srinadh Bhojanapalli +2
cs.LGstat.MLarXiv:1805.12076v12018
Necessary and Sufficient Conditions for Success of the Nuclear Norm Heuristic for Rank Minimization
Benjamin Recht, Weiyu Xu, Babak Hassibi
math.OCstat.COstat.MLarXiv:0809.1260v12008
Robust Federated Learning with Noisy Communication
Fan Ang, Li Chen, Nan Zhao +3
cs.LGstat.MLarXiv:1911.00251v12019
Offline RL Without Off-Policy Evaluation
David Brandfonbrener, William F. Whitney, Rajesh Ranganath +1
cs.LGstat.MLarXiv:2106.08909v32021
Structured Generative Models of Natural Source Code
Chris J. Maddison, Daniel Tarlow
cs.PLcs.LGstat.MLarXiv:1401.0514v22014
Method, Mind, and Morality: How People Make Sense of Artificial Intelligence
Jacy Reese Anthis, Erik Brynjolfsson, James Evans
cs.CYcs.AIcs.CLarXiv:2608.24748v12026
Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar +2
cs.AIcs.CLcs.CVarXiv:1707.09457v12017
Sequential Conditional Independence Testing with Machine Learning Models
Angel Reyero-Lobo, Michele Meziu, Sebastian Uriel Arias +1
math.STstat.MLstat.THarXiv:2610.11388v12026
Rollcast: Proper-Score Gated Rolling Anchors for Adaptive Probabilistic Time-Series Forecasting
Giancarlo Vercellino
stat.MLcs.LGstat.MEarXiv:2609.05561v12026
Short-term Load Forecasting with Deep Residual Networks
Kunjin Chen, Kunlong Chen, Qin Wang +3
stat.MLcs.LGstat.AParXiv:1805.11956v12018
Robustness May Be at Odds with Accuracy
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom +2
stat.MLcs.CVcs.LGarXiv:1805.12152v52018
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks
Chunyuan Li, Changyou Chen, David Carlson +1
stat.MLarXiv:1512.07666v12015
A General Theory of Equivariant CNNs on Homogeneous Spaces
Taco Cohen, Mario Geiger, Maurice Weiler
cs.LGcs.AIcs.CGarXiv:1811.02017v22018
Newton-Type Methods for Non-Convex Optimization Under Inexact Hessian Information
Peng Xu, Fred Roosta, Michael W. Mahoney
math.OCcs.CCcs.LGarXiv:1708.07164v42017
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control
Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty
cs.LGeess.SYphysics.comp-pharXiv:1909.12077v52019
Rényi Differential Privacy of the Sampled Gaussian Mechanism
Ilya Mironov, Kunal Talwar, Li Zhang
cs.LGcs.CRstat.MLarXiv:1908.10530v12019
Random Walks on Hypergraphs with Edge-Dependent Vertex Weights
Uthsav Chitra, Benjamin J Raphael
cs.LGcs.DMcs.SIarXiv:1905.08287v12019
On Penalty-based Bilevel Gradient Descent Method
Han Shen, Quan Xiao, Tianyi Chen
cs.LGmath.OCstat.MLarXiv:2302.05185v52023
Towards Sparse Hierarchical Graph Classifiers
Cătălina Cangea, Petar Veličković, Nikola Jovanović +2
stat.MLcs.AIcs.LGarXiv:1811.01287v12018
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification
Chaochao Chen, Jun Zhou, Longfei Zheng +7
cs.LGcs.CRstat.MLarXiv:2005.11903v32020
Why Is My Classifier Discriminatory?
Irene Chen, Fredrik D. Johansson, David Sontag
stat.MLcs.LGarXiv:1805.12002v22018
Multi-Turn On-Policy Distillation with Prefix Replay
Baohao Liao, Hanze Dong, Christof Monz +3
cs.LGcs.AIcs.CLarXiv:2607.04763v32026
Structured Neural Summarization
Patrick Fernandes, Miltiadis Allamanis, Marc Brockschmidt
cs.LGcs.CLcs.SEarXiv:1811.01824v42018
Pruning Neural Networks at Initialization: Why are We Missing the Mark?
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy +1
cs.LGcs.CVcs.NEarXiv:2009.08576v22020
The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint
Stephen Tu, Benjamin Recht
cs.LGmath.OCstat.MLarXiv:1812.03565v22018
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
Akara Supratak, Hao Dong, Chao Wu +1
stat.MLarXiv:1703.04046v22017
Counterfactual Fairness in Text Classification through Robustness
Sahaj Garg, Vincent Perot, Nicole Limtiaco +3
cs.LGstat.MLarXiv:1809.10610v22018
On the Expressive Power of Geometric Graph Neural Networks
Chaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis +2
cs.LGmath.GRstat.MLarXiv:2301.09308v32023
In Search of Lost Domain Generalization
Ishaan Gulrajani, David Lopez-Paz
cs.LGstat.MLarXiv:2007.01434v12020
Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing
Yuchen Zhang, Xi Chen, Dengyong Zhou +1
stat.MLarXiv:1406.3824v32014
Label Efficient Learning of Transferable Representations across Domains and Tasks
Zelun Luo, Yuliang Zou, Judy Hoffman +1
stat.MLcs.CVarXiv:1712.00123v12017
An analytic theory of generalization dynamics and transfer learning in deep linear networks
Andrew K. Lampinen, Surya Ganguli
stat.MLcs.LGarXiv:1809.10374v22018
A Unified Theory of Diversity in Ensemble Learning
Danny Wood, Tingting Mu, Andrew Webb +3
cs.LGcs.AIstat.MLarXiv:2301.03962v32023
A Simple Convolutional Generative Network for Next Item Recommendation
Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis +2
cs.IRcs.LGstat.MLarXiv:1808.05163v42018
Learning Montezuma's Revenge from a Single Demonstration
Tim Salimans, Richard Chen
cs.LGcs.AIcs.NEarXiv:1812.03381v12018
Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision
Hans Olischläger, Svenja Jedhoff, Šimon Kucharský +3
stat.MLcs.LGstat.COarXiv:2609.39525v12026

Machine Learning (stat)

Batch Active Learning Using Determinantal Point Processes

Measuring the Algorithmic Efficiency of Neural Networks

Heterogeneous domain adaptation: An unsupervised approach

Scaling provable adversarial defenses

Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment

LAIR-Net: Leaky Alignment-Impulse Residual Networks for Tabular Regression

Variational Policy Gradient Method for Reinforcement Learning with General Utilities

In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction

End-to-End Robotic Reinforcement Learning without Reward Engineering

Adversarially Learned Inference

On the Robustness of the Backdoor-based Watermarking in Deep Neural Networks

Meta-GNN: On Few-shot Node Classification in Graph Meta-learning

To understand deep learning we need to understand kernel learning

3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data

GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference

Soft Threshold Weight Reparameterization for Learnable Sparsity

Federated Asymptotics: a model to compare federated learning algorithms

Cautious Weight Decay

Multi-Task Learning with Deep Neural Networks: A Survey

From Bandits to Experts: On the Value of Side-Observations

Certified Robustness to Label-Flipping Attacks via Randomized Smoothing

MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling

High-accuracy sampling for diffusion models and log-concave distributions

Tensor Logic: The Language of AI

Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks

Necessary and Sufficient Conditions for Success of the Nuclear Norm Heuristic for Rank Minimization

Robust Federated Learning with Noisy Communication

Offline RL Without Off-Policy Evaluation

Structured Generative Models of Natural Source Code

Method, Mind, and Morality: How People Make Sense of Artificial Intelligence

Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints

Sequential Conditional Independence Testing with Machine Learning Models

Rollcast: Proper-Score Gated Rolling Anchors for Adaptive Probabilistic Time-Series Forecasting

Short-term Load Forecasting with Deep Residual Networks

Robustness May Be at Odds with Accuracy

Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks

A General Theory of Equivariant CNNs on Homogeneous Spaces

Newton-Type Methods for Non-Convex Optimization Under Inexact Hessian Information

Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control

Rényi Differential Privacy of the Sampled Gaussian Mechanism

Random Walks on Hypergraphs with Edge-Dependent Vertex Weights

On Penalty-based Bilevel Gradient Descent Method

Towards Sparse Hierarchical Graph Classifiers

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification

Why Is My Classifier Discriminatory?

Multi-Turn On-Policy Distillation with Prefix Replay

Structured Neural Summarization

Pruning Neural Networks at Initialization: Why are We Missing the Mark?

The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint

DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

Counterfactual Fairness in Text Classification through Robustness

On the Expressive Power of Geometric Graph Neural Networks

In Search of Lost Domain Generalization

Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing

Label Efficient Learning of Transferable Representations across Domains and Tasks

An analytic theory of generalization dynamics and transfer learning in deep linear networks

A Unified Theory of Diversity in Ensemble Learning

A Simple Convolutional Generative Network for Next Item Recommendation

Learning Montezuma's Revenge from a Single Demonstration

Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision