Machine Learning

Papers filed under cs.LG 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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7,741 to 7,800 of 20,193

An Actor-Critic Algorithm for Sequence Prediction
Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu +5
cs.LGarXiv:1607.07086v32016
Generative Adversarial Imitation Learning
Jonathan Ho, Stefano Ermon
cs.LGcs.AIarXiv:1606.03476v12016
Unifying Count-Based Exploration and Intrinsic Motivation
Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski +3
cs.AIcs.LGstat.MLarXiv:1606.01868v22016
Adversarial Feature Learning
Jeff Donahue, Philipp Krähenbühl, Trevor Darrell
cs.LGcs.AIcs.CVarXiv:1605.09782v72016
Fairness in Learning: Classic and Contextual Bandits
Matthew Joseph, Michael Kearns, Jamie Morgenstern +1
cs.LGstat.MLarXiv:1605.07139v22016
Deep Learning without Poor Local Minima
Kenji Kawaguchi
stat.MLcs.LGmath.OCarXiv:1605.07110v32016
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
Lisha Li, Kevin Jamieson, Giulia DeSalvo +2
cs.LGstat.MLarXiv:1603.06560v42016
Bayesian Consensus Clustering
Eric F. Lock, David B. Dunson
stat.MLcs.LGarXiv:1302.7280v12013
Rényi Divergence Variational Inference
Yingzhen Li, Richard E. Turner
stat.MLcs.LGarXiv:1602.02311v32016
Feature Selection: A Data Perspective
Jundong Li, Kewei Cheng, Suhang Wang +4
cs.LGarXiv:1601.07996v52016
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification
André F. T. Martins, Ramón Fernandez Astudillo
cs.CLcs.LGstat.MLarXiv:1602.02068v22016
DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments
Yuxiang Zheng, Dayuan Fu, Xiangkun Hu +4
cs.AIcs.CLcs.LGarXiv:2504.03160v42025
Gated Graph Sequence Neural Networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt +1
cs.LGcs.AIcs.NEarXiv:1511.05493v42015
The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems
Ryan Lowe, Nissan Pow, Iulian Serban +1
cs.CLcs.AIcs.LGarXiv:1506.08909v32015
Hinge-Loss Markov Random Fields and Probabilistic Soft Logic
Stephen H. Bach, Matthias Broecheler, Bert Huang +1
cs.LGcs.AIstat.MLarXiv:1505.04406v32015
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition
Rong Ge, Furong Huang, Chi Jin +1
cs.LGmath.OCstat.MLarXiv:1503.02101v12015
Automatic differentiation in machine learning: a survey
Atilim Gunes Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul +1
cs.SCcs.LGstat.MLarXiv:1502.05767v42015
Non-stochastic Best Arm Identification and Hyperparameter Optimization
Kevin Jamieson, Ameet Talwalkar
cs.LGstat.MLarXiv:1502.07943v12015
Deep Learning with Limited Numerical Precision
Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan +1
cs.LGcs.NEstat.MLarXiv:1502.02551v12015
New insights and perspectives on the natural gradient method
James Martens
cs.LGstat.MLarXiv:1412.1193v112014
The Loss Surfaces of Multilayer Networks
Anna Choromanska, Mikael Henaff, Michael Mathieu +2
cs.LGarXiv:1412.0233v32014
Breaking the Curse of Dimensionality with Convex Neural Networks
Francis Bach
cs.LGmath.OCmath.STarXiv:1412.8690v22014
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization
Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
cs.LGmath.OCarXiv:1109.5647v72011
Generalized Low Rank Models
Madeleine Udell, Corinne Horn, Reza Zadeh +1
stat.MLcs.LGmath.OCarXiv:1410.0342v42014
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models
Emilie Kaufmann, Olivier Cappé, Aurélien Garivier
stat.MLcs.LGarXiv:1407.4443v22014
Minimizing Finite Sums with the Stochastic Average Gradient
Mark Schmidt, Nicolas Le Roux, Francis Bach
math.OCcs.LGstat.COarXiv:1309.2388v22013
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm
Deanna Needell, Nathan Srebro, Rachel Ward
math.NAcs.CVcs.LGarXiv:1310.5715v52013
Phase Retrieval using Alternating Minimization
Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi
stat.MLcs.ITcs.LGarXiv:1306.0160v22013
Bandits with Knapsacks
Ashwinkumar Badanidiyuru, Robert Kleinberg, Aleksandrs Slivkins
cs.DScs.LGarXiv:1305.2545v82013
Tensor decompositions for learning latent variable models
Anima Anandkumar, Rong Ge, Daniel Hsu +2
cs.LGmath.NAstat.MLarXiv:1210.7559v42012
A Widely Applicable Bayesian Information Criterion
Sumio Watanabe
cs.LGstat.MLarXiv:1208.6338v12012
Sparse Approximation via Penalty Decomposition Methods
Zhaosong Lu, Yong Zhang
cs.LGmath.OCstat.COarXiv:1205.2334v22012
Learning high-dimensional directed acyclic graphs with latent and selection variables
Diego Colombo, Marloes H. Maathuis, Markus Kalisch +1
stat.MEcs.LGmath.STarXiv:1104.5617v32011
Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions
Alekh Agarwal, Sahand N. Negahban, Martin J. Wainwright
stat.MLcs.ITcs.LGarXiv:1102.4807v32011
Optimization with Sparsity-Inducing Penalties
Francis Bach, Rodolphe Jenatton, Julien Mairal +1
cs.LGmath.OCstat.MLarXiv:1108.0775v22011
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
Feng Niu, Benjamin Recht, Christopher Re +1
math.OCcs.LGarXiv:1106.5730v22011
Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization
Daniel Golovin, Andreas Krause
cs.LGcs.AIcs.DSarXiv:1003.3967v52010
A Dynamic Near-Optimal Algorithm for Online Linear Programming
Shipra Agrawal, Zizhuo Wang, Yinyu Ye
cs.DScs.LGarXiv:0911.2974v32009
Contextual Bandits with Similarity Information
Aleksandrs Slivkins
cs.DScs.LGarXiv:0907.3986v52009
Matrix Completion from Noisy Entries
Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh
cs.LGstat.MLarXiv:0906.2027v22009
HVI: A New Color Space for Low-light Image Enhancement
Qingsen Yan, Yixu Feng, Cheng Zhang +6
cs.CVcs.AIcs.LGarXiv:2502.20272v22025
Masked Face Recognition for Secure Authentication
Aqeel Anwar, Arijit Raychowdhury
cs.CVcs.LGeess.IVarXiv:2008.11104v12020
Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions
Jaeyeon Kim, Kulin Shah, Vasilis Kontonis +2
cs.LGarXiv:2502.06768v32025
Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari +12
cs.LGeess.IVarXiv:2007.10785v72020
Scalable Best-of-N Selection for Large Language Models via Self-Certainty
Zhewei Kang, Xuandong Zhao, Dawn Song
cs.CLcs.AIcs.LGarXiv:2502.18581v32025
Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models
Lucy Xiaoyang Shi, Brian Ichter, Michael Equi +12
cs.ROcs.AIcs.LGarXiv:2502.19417v22025
Learning Debiased Representation via Disentangled Feature Augmentation
Jungsoo Lee, Eungyeup Kim, Juyoung Lee +2
cs.LGarXiv:2107.01372v22021
Path Integral Sampler: a stochastic control approach for sampling
Qinsheng Zhang, Yongxin Chen
cs.LGarXiv:2111.15141v22021
d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning
Siyan Zhao, Devaansh Gupta, Qinqing Zheng +1
cs.CLcs.LGarXiv:2504.12216v22025
ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills
Tairan He, Jiawei Gao, Wenli Xiao +15
cs.ROcs.AIcs.LGarXiv:2502.01143v32025
Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction
Yong Lin, Shange Tang, Bohan Lyu +17
cs.LGcs.AIarXiv:2508.03613v12025
Quantum-Grassmann-Plucker Token Mixing for Deep Learning-Based Post-Disaster Damage Assessment
Kooroush Farahkhah, Umut Lagap, Taha Rezaei +1
cs.CVcs.LGarXiv:2608.30633v12026
Neural ODE enhanced linear mixed effect models for estimating complex association patterns of time-varying covariates with the marker trajectory
Zhe Aurore Li, Quentin Clairon, Cécilia Samieri +3
stat.MLcs.LGarXiv:2608.29714v12026
Muon with Finite Newton-Schulz: The Smoothing Benefit in Nonsmooth Nonconvex Optimization
Mingyi Li, Taira Tsuchiya
cs.LGmath.OCstat.MLarXiv:2608.26288v12026
Sharp Minimax Regret for Infinite-Memory Logistic Prediction
Vaneet Aggarwal
cs.ITcs.LGarXiv:2608.26515v12026
Modeling spatio-temporal locality in multi-step forecasting of geo-referenced time series
Annunziata D'Aversa, Gianvito Pio, Michelangelo Ceci
cs.LGarXiv:2608.25698v12026
Tropospheric temperature and humidity profile retrieval from Meteosat Flexible Combined Imager based on deep learning
Alejandro Salgueiro, Johannes Rausch, Julie Thérèse Villinger +1
cs.LGphysics.ao-pharXiv:2608.25700v12026
LION: A Clifford Neural Paradigm for Multimodal-Attributed Graph Learning
Xunkai Li, Zekai Chen, Zhengyu Wu +6
cs.LGarXiv:2608.24795v12026
Decoupling candidate dual AGN from chance superpositions in the GOTHIC survey via a deep-learning framework
Bhavesh Mukheja, Snehanshu Saha, Anwesh Bhattacharya +3
astro-ph.GAcs.CVcs.LGarXiv:2608.24164v12026
Optimal Alternating Regret for Online Learning and Games
Yixin Tao, Weiqiang Zheng
cs.LGcs.GTstat.MLarXiv:2608.24731v12026

Machine Learning

An Actor-Critic Algorithm for Sequence Prediction

Generative Adversarial Imitation Learning

Unifying Count-Based Exploration and Intrinsic Motivation

Adversarial Feature Learning

Fairness in Learning: Classic and Contextual Bandits

Deep Learning without Poor Local Minima

Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization

Bayesian Consensus Clustering

Rényi Divergence Variational Inference

Feature Selection: A Data Perspective

From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification

DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments

Gated Graph Sequence Neural Networks

The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems

Hinge-Loss Markov Random Fields and Probabilistic Soft Logic

Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition

Automatic differentiation in machine learning: a survey

Non-stochastic Best Arm Identification and Hyperparameter Optimization

Deep Learning with Limited Numerical Precision

New insights and perspectives on the natural gradient method

The Loss Surfaces of Multilayer Networks

Breaking the Curse of Dimensionality with Convex Neural Networks

Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization

Generalized Low Rank Models

On the Complexity of Best Arm Identification in Multi-Armed Bandit Models

Minimizing Finite Sums with the Stochastic Average Gradient

Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm

Phase Retrieval using Alternating Minimization

Bandits with Knapsacks

Tensor decompositions for learning latent variable models

A Widely Applicable Bayesian Information Criterion

Sparse Approximation via Penalty Decomposition Methods

Learning high-dimensional directed acyclic graphs with latent and selection variables

Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions

Optimization with Sparsity-Inducing Penalties

HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization

A Dynamic Near-Optimal Algorithm for Online Linear Programming

Contextual Bandits with Similarity Information

Matrix Completion from Noisy Entries

HVI: A New Color Space for Low-light Image Enhancement

Masked Face Recognition for Secure Authentication

Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions

Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review

Scalable Best-of-N Selection for Large Language Models via Self-Certainty

Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models

Learning Debiased Representation via Disentangled Feature Augmentation

Path Integral Sampler: a stochastic control approach for sampling

d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning

ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills

Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction

Quantum-Grassmann-Plucker Token Mixing for Deep Learning-Based Post-Disaster Damage Assessment

Neural ODE enhanced linear mixed effect models for estimating complex association patterns of time-varying covariates with the marker trajectory

Muon with Finite Newton-Schulz: The Smoothing Benefit in Nonsmooth Nonconvex Optimization

Sharp Minimax Regret for Infinite-Memory Logistic Prediction

Modeling spatio-temporal locality in multi-step forecasting of geo-referenced time series

Tropospheric temperature and humidity profile retrieval from Meteosat Flexible Combined Imager based on deep learning

LION: A Clifford Neural Paradigm for Multimodal-Attributed Graph Learning

Decoupling candidate dual AGN from chance superpositions in the GOTHIC survey via a deep-learning framework

Optimal Alternating Regret for Online Learning and Games