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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7,441 to 7,500 of 20,014

Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning
Xiao Wang, Nian Liu, Hui Han +1
cs.LGarXiv:2105.09111v12021
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang +2
cs.LGarXiv:2102.07623v22021
BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
Yuhang Li, Ruihao Gong, Xu Tan +6
cs.LGcs.CVarXiv:2102.05426v22021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks
Sifan Wang, Hanwen Wang, Paris Perdikaris
cs.LGcs.AIstat.MLarXiv:2012.10047v12020
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander D'Amour, Katherine Heller, Dan Moldovan +37
cs.LGstat.MLarXiv:2011.03395v22020
pixelNeRF: Neural Radiance Fields from One or Few Images
Alex Yu, Vickie Ye, Matthew Tancik +1
cs.CVcs.GRcs.LGarXiv:2012.02190v32020
MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis
Devamanyu Hazarika, Roger Zimmermann, Soujanya Poria
cs.CLcs.LGarXiv:2005.03545v32020
Rethinking Attention with Performers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan +10
cs.LGcs.CLstat.MLarXiv:2009.14794v42020
A rigorous and robust quantum speed-up in supervised machine learning
Yunchao Liu, Srinivasan Arunachalam, Kristan Temme
quant-phcs.LGarXiv:2010.02174v22020
Understanding the Role of Individual Units in a Deep Neural Network
David Bau, Jun-Yan Zhu, Hendrik Strobelt +3
cs.CVcs.LGcs.NEarXiv:2009.05041v22020
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems
Ruoxi Wang, Rakesh Shivanna, Derek Z. Cheng +4
cs.IRcs.LGstat.MLarXiv:2008.13535v22020
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
Shai Shalev-Shwartz, Tong Zhang
stat.MLcs.LGmath.OCarXiv:1209.1873v22012
QPLEX: Duplex Dueling Multi-Agent Q-Learning
Jianhao Wang, Zhizhou Ren, Terry Liu +2
cs.LGcs.AIcs.MAarXiv:2008.01062v32020
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice
Li Yang, Abdallah Shami
cs.LGstat.MLarXiv:2007.15745v32020
A Decade of Social Bot Detection
Stefano Cresci
cs.CYcs.HCcs.LGarXiv:2007.03604v22020
Early-Learning Regularization Prevents Memorization of Noisy Labels
Sheng Liu, Jonathan Niles-Weed, Narges Razavian +1
cs.LGcs.CVstat.MLarXiv:2007.00151v22020
Personalized Federated Learning with Moreau Envelopes
Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen
cs.LGcs.DCstat.MLarXiv:2006.08848v32020
Bootstrap your own latent: A new approach to self-supervised Learning
Jean-Bastien Grill, Florian Strub, Florent Altché +11
cs.LGcs.CVstat.MLarXiv:2006.07733v32020
Adaptive Universal Generalized PageRank Graph Neural Network
Eli Chien, Jianhao Peng, Pan Li +1
cs.LGstat.MLarXiv:2006.07988v62020
TACTO: A Fast, Flexible, and Open-source Simulator for High-Resolution Vision-based Tactile Sensors
Shaoxiong Wang, Mike Lambeta, Po-Wei Chou +1
cs.ROcs.LGstat.MLarXiv:2012.08456v22020
Conservative Q-Learning for Offline Reinforcement Learning
Aviral Kumar, Aurick Zhou, George Tucker +1
cs.LGstat.MLarXiv:2006.04779v32020
An Efficient Framework for Clustered Federated Learning
Avishek Ghosh, Jichan Chung, Dong Yin +1
stat.MLcs.LGarXiv:2006.04088v22020
Adaptive Personalized Federated Learning
Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi
cs.LGcs.DCstat.MLarXiv:2003.13461v32020
Serving DNNs like Clockwork: Performance Predictability from the Bottom Up
Arpan Gujarati, Reza Karimi, Safya Alzayat +4
cs.DCcs.LGarXiv:2006.02464v22020
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
Zonghan Wu, Shirui Pan, Guodong Long +3
cs.LGstat.MLarXiv:2005.11650v12020
Universal Differential Equations for Scientific Machine Learning
Christopher Rackauckas, Yingbo Ma, Julius Martensen +6
cs.LGmath.DSq-bio.QMarXiv:2001.04385v42020
Personalized Federated Learning: A Meta-Learning Approach
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar
cs.LGmath.OCstat.MLarXiv:2002.07948v42020
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez, Pierre Boyeau, Nir Yosef +2
stat.MLcs.AIcs.LGarXiv:2002.07217v32020
MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding
Xinyu Fu, Jiani Zhang, Ziqiao Meng +1
cs.SIcs.LGarXiv:2002.01680v22020
Think Locally, Act Globally: Federated Learning with Local and Global Representations
Paul Pu Liang, Terrance Liu, Liu Ziyin +5
cs.LGcs.DCstat.MLarXiv:2001.01523v32020
Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)
Jamshed Memon, Maira Sami, Rizwan Ahmed Khan
cs.CVcs.LGarXiv:2001.00139v12020
Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting
Bryan Lim, Sercan O. Arik, Nicolas Loeff +1
stat.MLcs.LGarXiv:1912.09363v32019
Recurrent Neural Networks (RNNs): A gentle Introduction and Overview
Robin M. Schmidt
cs.LGstat.MLarXiv:1912.05911v12019
Training Deep Learning Models with Norm-Constrained LMOs
Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos +3
cs.LGmath.OCarXiv:2502.07529v22025
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
Tianhe Yu, Deirdre Quillen, Zhanpeng He +7
cs.LGcs.AIcs.ROarXiv:1910.10897v22019
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto +1
cs.LGstat.MLarXiv:1911.08731v22019
Once-for-All: Train One Network and Specialize it for Efficient Deployment
Han Cai, Chuang Gan, Tianzhe Wang +2
cs.LGcs.CVstat.MLarXiv:1908.09791v52019
Hyperbolic Graph Convolutional Neural Networks
Ines Chami, Rex Ying, Christopher Ré +1
cs.LGstat.MLarXiv:1910.12933v12019
Predicting Subsurface Abnormalities Growth using Physics-Informed Neural Networks
Mehrdad Shafiei Dizaji, Hoda Azari
cs.LGarXiv:2609.01417v12026
Representation Learning: A Review and New Perspectives
Yoshua Bengio, Aaron Courville, Pascal Vincent
cs.LGarXiv:1206.5538v32012
Pseudo-likelihood methods for community detection in large sparse networks
Arash A. Amini, Aiyou Chen, Peter J. Bickel +1
cs.SIcs.LGmath.STarXiv:1207.2340v32012
Tighter Theory for Local SGD on Identical and Heterogeneous Data
Ahmed Khaled, Konstantin Mishchenko, Peter Richtárik
cs.LGcs.DCmath.NAarXiv:1909.04746v42019
On the Variance of the Adaptive Learning Rate and Beyond
Liyuan Liu, Haoming Jiang, Pengcheng He +4
cs.LGcs.CLstat.MLarXiv:1908.03265v42019
GraphSAINT: Graph Sampling Based Inductive Learning Method
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava +2
cs.LGstat.MLarXiv:1907.04931v42019
Large Scale Adversarial Representation Learning
Jeff Donahue, Karen Simonyan
cs.CVcs.LGstat.MLarXiv:1907.02544v22019
On the Convergence of FedAvg on Non-IID Data
Xiang Li, Kaixuan Huang, Wenhao Yang +2
stat.MLcs.LGmath.OCarXiv:1907.02189v42019
Does Learning Require Memorization? A Short Tale about a Long Tail
Vitaly Feldman
cs.LGstat.MLarXiv:1906.05271v42019
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels
Simon S. Du, Kangcheng Hou, Barnabás Póczos +3
cs.LGcs.AIcs.CVarXiv:1905.13192v22019
Text Classification Algorithms: A Survey
Kamran Kowsari, Kiana Jafari Meimandi, Mojtaba Heidarysafa +3
cs.LGcs.AIcs.CLarXiv:1904.08067v52019
Provably Powerful Graph Networks
Haggai Maron, Heli Ben-Hamu, Hadar Serviansky +1
cs.LGstat.MLarXiv:1905.11136v42019
Deep Reinforcement Learning for Sepsis Treatment
Aniruddh Raghu, Matthieu Komorowski, Imran Ahmed +3
cs.AIcs.LGarXiv:1711.09602v12017
Mercury: Ultra-Fast Language Models Based on Diffusion
Inception Labs, Samar Khanna, Siddhant Kharbanda +10
cs.CLcs.AIcs.LGarXiv:2506.17298v12025
On Exact Computation with an Infinitely Wide Neural Net
Sanjeev Arora, Simon S. Du, Wei Hu +3
cs.LGcs.CVcs.NEarXiv:1904.11955v22019
Embarrassingly Shallow Autoencoders for Sparse Data
Harald Steck
cs.IRcs.LGstat.MLarXiv:1905.03375v12019
CopyShield: A Cross-Level Benchmark of Copyright Defenses in LLMs
Maryam Alshehyari, Dushyant Singh Chauhan, Samuele Poppi +3
cs.LGarXiv:2609.01161v12026
On the Convergence of Adam and Beyond
Sashank J. Reddi, Satyen Kale, Sanjiv Kumar
cs.LGmath.OCstat.MLarXiv:1904.09237v12019
A Survey on Traffic Signal Control Methods
Hua Wei, Guanjie Zheng, Vikash Gayah +1
cs.LGcs.AIstat.MLarXiv:1904.08117v32019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Trevor Hastie, Andrea Montanari, Saharon Rosset +1
math.STcs.LGstat.MLarXiv:1903.08560v52019
Three scenarios for continual learning
Gido M. van de Ven, Andreas S. Tolias
cs.LGcs.AIcs.CVarXiv:1904.07734v12019
ICLabel: An automated electroencephalographic independent component classifier, dataset, and website
Luca Pion-Tonachini, Ken Kreutz-Delgado, Scott Makeig
eess.SPcs.LGstat.MLarXiv:1901.07915v22019

Machine Learning

Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning

FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction

On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks

Underspecification Presents Challenges for Credibility in Modern Machine Learning

pixelNeRF: Neural Radiance Fields from One or Few Images

MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis

Rethinking Attention with Performers

A rigorous and robust quantum speed-up in supervised machine learning

Understanding the Role of Individual Units in a Deep Neural Network

DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems

Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization

QPLEX: Duplex Dueling Multi-Agent Q-Learning

On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice

A Decade of Social Bot Detection

Early-Learning Regularization Prevents Memorization of Noisy Labels

Personalized Federated Learning with Moreau Envelopes

Bootstrap your own latent: A new approach to self-supervised Learning

Adaptive Universal Generalized PageRank Graph Neural Network

TACTO: A Fast, Flexible, and Open-source Simulator for High-Resolution Vision-based Tactile Sensors

Conservative Q-Learning for Offline Reinforcement Learning

An Efficient Framework for Clustered Federated Learning

Adaptive Personalized Federated Learning

Serving DNNs like Clockwork: Performance Predictability from the Bottom Up

Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

Universal Differential Equations for Scientific Machine Learning

Personalized Federated Learning: A Meta-Learning Approach

Decision-Making with Auto-Encoding Variational Bayes

MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding

Think Locally, Act Globally: Federated Learning with Local and Global Representations

Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)

Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting

Recurrent Neural Networks (RNNs): A gentle Introduction and Overview

Training Deep Learning Models with Norm-Constrained LMOs

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

Once-for-All: Train One Network and Specialize it for Efficient Deployment

Hyperbolic Graph Convolutional Neural Networks

Predicting Subsurface Abnormalities Growth using Physics-Informed Neural Networks

Representation Learning: A Review and New Perspectives

Pseudo-likelihood methods for community detection in large sparse networks

Tighter Theory for Local SGD on Identical and Heterogeneous Data

On the Variance of the Adaptive Learning Rate and Beyond

GraphSAINT: Graph Sampling Based Inductive Learning Method

Large Scale Adversarial Representation Learning

On the Convergence of FedAvg on Non-IID Data

Does Learning Require Memorization? A Short Tale about a Long Tail

Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels

Text Classification Algorithms: A Survey

Provably Powerful Graph Networks

Deep Reinforcement Learning for Sepsis Treatment

Mercury: Ultra-Fast Language Models Based on Diffusion

On Exact Computation with an Infinitely Wide Neural Net

Embarrassingly Shallow Autoencoders for Sparse Data

CopyShield: A Cross-Level Benchmark of Copyright Defenses in LLMs

On the Convergence of Adam and Beyond

A Survey on Traffic Signal Control Methods

Surprises in High-Dimensional Ridgeless Least Squares Interpolation

Three scenarios for continual learning

ICLabel: An automated electroencephalographic independent component classifier, dataset, and website