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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8,041 to 8,100 of 20,199

Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
Xiaofei Wang, Yiwen Han, Victor C. M. Leung +3
cs.NIcs.LGarXiv:1907.08349v32019
Invariant Risk Minimization
Martin Arjovsky, Léon Bottou, Ishaan Gulrajani +1
stat.MLcs.AIcs.LGarXiv:1907.02893v32019
A Survey of Optimization Methods from a Machine Learning Perspective
Shiliang Sun, Zehui Cao, Han Zhu +1
cs.LGmath.OCstat.MLarXiv:1906.06821v22019
Deep Learning for Spatio-Temporal Data Mining: A Survey
Senzhang Wang, Jiannong Cao, Philip S. Yu
cs.LGstat.MLarXiv:1906.04928v22019
Deep Network Approximation Characterized by Number of Neurons
Zuowei Shen, Haizhao Yang, Shijun Zhang
math.NAcs.LGarXiv:1906.05497v52019
Unlabeled Data Improves Adversarial Robustness
Yair Carmon, Aditi Raghunathan, Ludwig Schmidt +2
stat.MLcs.CVcs.LGarXiv:1905.13736v42019
MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe
Tianyu Yu, Zefan Wang, Chongyi Wang +31
cs.LGcs.CVarXiv:2509.18154v12025
Client-Edge-Cloud Hierarchical Federated Learning
Lumin Liu, Jun Zhang, S. H. Song +1
cs.NIcs.LGarXiv:1905.06641v22019
Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control
Tianshu Chu, Jie Wang, Lara Codecà +1
cs.LGstat.MLarXiv:1903.04527v12019
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu, Shirui Pan, Fengwen Chen +3
cs.LGstat.MLarXiv:1901.00596v42019
Robust and Communication-Efficient Federated Learning from Non-IID Data
Felix Sattler, Simon Wiedemann, Klaus-Robert Müller +1
cs.LGcs.AIcs.DCarXiv:1903.02891v12019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks
Sanjeev Arora, Simon S. Du, Wei Hu +2
cs.LGcs.NEstat.MLarXiv:1901.08584v22019
Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network
Jussi Leinonen, Daniele Nerini, Alexis Berne
eess.IVcs.LGphysics.ao-pharXiv:2005.10374v42020
Broadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version)
Guangxu Zhu, Yong Wang, Kaibin Huang
cs.ITcs.LGarXiv:1812.11494v32018
TextBugger: Generating Adversarial Text Against Real-world Applications
Jinfeng Li, Shouling Ji, Tianyu Du +2
cs.CRcs.CLcs.LGarXiv:1812.05271v12018
SNAS: Stochastic Neural Architecture Search
Sirui Xie, Hehui Zheng, Chunxiao Liu +1
cs.LGcs.AIstat.MLarXiv:1812.09926v32018
Deep Learning on Graphs: A Survey
Ziwei Zhang, Peng Cui, Wenwu Zhu
cs.LGcs.SIstat.MLarXiv:1812.04202v32018
Entropy-Aware On-Policy Distillation of Language Models
Woogyeol Jin, Taywon Min, Yongjin Yang +5
cs.LGcs.CLarXiv:2603.07079v32026
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers
Zeyuan Allen-Zhu, Yuanzhi Li, Yingyu Liang
cs.LGcs.DScs.NEarXiv:1811.04918v62018
Neural Lander: Stable Drone Landing Control using Learned Dynamics
Guanya Shi, Xichen Shi, Michael O'Connell +5
cs.ROcs.LGarXiv:1811.08027v22018
Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation
Linfeng Zhang, De-Ye Lin, Han Wang +2
physics.comp-phcond-mat.mtrl-scics.LGarXiv:1810.11890v22018
Activation Functions: Comparison of trends in Practice and Research for Deep Learning
Chigozie Nwankpa, Winifred Ijomah, Anthony Gachagan +1
cs.LGcs.CVarXiv:1811.03378v12018
Agentic Misalignment: How LLMs Could Be Insider Threats
Aengus Lynch, Benjamin Wright, Caleb Larson +5
cs.CRcs.AIcs.LGarXiv:2510.05179v22025
A General Theory of Equivariant CNNs on Homogeneous Spaces
Taco Cohen, Mario Geiger, Maurice Weiler
cs.LGcs.AIcs.CGarXiv:1811.02017v22018
Deep Learning with Long Short-Term Memory for Time Series Prediction
Yuxiu Hua, Zhifeng Zhao, Rongpeng Li +3
cs.NEcs.LGarXiv:1810.10161v12018
SLAYER: Spike Layer Error Reassignment in Time
Sumit Bam Shrestha, Garrick Orchard
cs.NEcs.LGstat.MLarXiv:1810.08646v12018
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Nguyen Cong Luong, Dinh Thai Hoang, Shimin Gong +4
cs.NIcs.LGarXiv:1810.07862v12018
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
Christopher Morris, Martin Ritzert, Matthias Fey +4
cs.LGcs.AIcs.CVarXiv:1810.02244v52018
In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning
Xiaofei Wang, Yiwen Han, Chenyang Wang +3
cs.NIcs.LGarXiv:1809.07857v22018
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
Yi Luo, Nima Mesgarani
cs.SDcs.LGeess.ASarXiv:1809.07454v32018
Collaborative Deep Learning in Fixed Topology Networks
Zhanhong Jiang, Aditya Balu, Chinmay Hegde +1
stat.MLcs.LGarXiv:1706.07880v12017
CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE)
Chenyu You, Guang Li, Yi Zhang +9
eess.IVcs.CVcs.LGarXiv:1808.04256v32018
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network
Alex Sherstinsky
cs.LGstat.MLarXiv:1808.03314v102018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data
Yuanzhi Li, Yingyu Liang
cs.LGstat.MLarXiv:1808.01204v32018
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord, Yazhe Li, Oriol Vinyals
cs.LGstat.MLarXiv:1807.03748v22018
Federated Learning with Non-IID Data
Yue Zhao, Meng Li, Liangzhen Lai +3
cs.LGstat.MLarXiv:1806.00582v22018
Understanding and Overcoming the Challenges of Efficient Transformer Quantization
Yelysei Bondarenko, Markus Nagel, Tijmen Blankevoort
cs.LGcs.AIcs.CLarXiv:2109.12948v12021
Optimized Computation Offloading Performance in Virtual Edge Computing Systems via Deep Reinforcement Learning
Xianfu Chen, Honggang Zhang, Celimuge Wu +3
cs.LGcs.AIstat.MLarXiv:1805.06146v12018
Deep Learning in Mobile and Wireless Networking: A Survey
Chaoyun Zhang, Paul Patras, Hamed Haddadi
cs.NIcs.LGarXiv:1803.04311v32018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang, Tiffany Tuor, Theodoros Salonidis +4
cs.DCcs.LGmath.OCarXiv:1804.05271v32018
Attention, Learn to Solve Routing Problems!
Wouter Kool, Herke van Hoof, Max Welling
stat.MLcs.LGarXiv:1803.08475v32018
Deep Auxiliary Learning for Visual Localization and Odometry
Abhinav Valada, Noha Radwan, Wolfram Burgard
cs.ROcs.LGarXiv:1803.03642v12018
Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis
Tal Ben-Nun, Torsten Hoefler
cs.LGcs.CVcs.DCarXiv:1802.09941v22018
A DIRT-T Approach to Unsupervised Domain Adaptation
Rui Shu, Hung H. Bui, Hirokazu Narui +1
stat.MLcs.CVcs.LGarXiv:1802.08735v22018
Stronger generalization bounds for deep nets via a compression approach
Sanjeev Arora, Rong Ge, Behnam Neyshabur +1
cs.LGarXiv:1802.05296v42018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes, John Healy, James Melville
stat.MLcs.CGcs.LGarXiv:1802.03426v32018
Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks
Jianhao Ding, Zhaofei Yu, Yonghong Tian +1
cs.NEcs.AIcs.CVarXiv:2105.11654v12021
IDEEA: training-free Input-Dependent stEEring via Activation cluster matching
Zheng Wang, Muchen Li, Renjie Liao +1
cs.CLcs.LGarXiv:2609.02089v12026
Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations
Maziar Raissi, Paris Perdikaris, George Em Karniadakis
cs.AIcs.LGmath.DSarXiv:1711.10561v12017
DeepSign: Deep Learning for Automatic Malware Signature Generation and Classification
Eli David, Nathan S. Netanyahu
cs.CRcs.LGcs.NEarXiv:1711.08336v22017
Advances in Variational Inference
Cheng Zhang, Judith Butepage, Hedvig Kjellstrom +1
cs.LGstat.MLarXiv:1711.05597v32017
Certifying Some Distributional Robustness with Principled Adversarial Training
Aman Sinha, Hongseok Namkoong, Riccardo Volpi +1
stat.MLcs.LGarXiv:1710.10571v52017
Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives
A. Cichocki, A-H. Phan, Q. Zhao +4
math.NAcs.LGarXiv:1708.09165v12017
Real-Time Execution of Action Chunking Flow Policies
Kevin Black, Manuel Y. Galliker, Sergey Levine
cs.ROcs.AIcs.LGarXiv:2506.07339v22025
Lipschitz Continuity in Model-based Reinforcement Learning
Kavosh Asadi, Dipendra Misra, Michael L. Littman
cs.LGcs.AIstat.MLarXiv:1804.07193v32018
End-to-end Driving via Conditional Imitation Learning
Felipe Codevilla, Matthias Müller, Antonio López +2
cs.ROcs.CVcs.LGarXiv:1710.02410v22017
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
Maximilian Igl, Kamil Ciosek, Yingzhen Li +4
cs.LGcs.AIstat.MLarXiv:1910.12911v12019
Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta +4
cs.LGcs.AIcs.ROarXiv:1709.10087v22017
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
MiniMax, :, Aili Chen +125
cs.CLcs.LGarXiv:2506.13585v12025
EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification
Patrick Helber, Benjamin Bischke, Andreas Dengel +1
cs.CVcs.LGarXiv:1709.00029v22017

Machine Learning

Convergence of Edge Computing and Deep Learning: A Comprehensive Survey

Invariant Risk Minimization

A Survey of Optimization Methods from a Machine Learning Perspective

Deep Learning for Spatio-Temporal Data Mining: A Survey

Deep Network Approximation Characterized by Number of Neurons

Unlabeled Data Improves Adversarial Robustness

MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe

Client-Edge-Cloud Hierarchical Federated Learning

Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control

A Comprehensive Survey on Graph Neural Networks

Robust and Communication-Efficient Federated Learning from Non-IID Data

Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks

Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network

Broadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version)

TextBugger: Generating Adversarial Text Against Real-world Applications

SNAS: Stochastic Neural Architecture Search

Deep Learning on Graphs: A Survey

Entropy-Aware On-Policy Distillation of Language Models

Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers

Neural Lander: Stable Drone Landing Control using Learned Dynamics

Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation

Activation Functions: Comparison of trends in Practice and Research for Deep Learning

Agentic Misalignment: How LLMs Could Be Insider Threats

A General Theory of Equivariant CNNs on Homogeneous Spaces

Deep Learning with Long Short-Term Memory for Time Series Prediction

SLAYER: Spike Layer Error Reassignment in Time

Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks

In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning

Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation

Collaborative Deep Learning in Fixed Topology Networks

CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE)

Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network

Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data

Representation Learning with Contrastive Predictive Coding

Federated Learning with Non-IID Data

Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Optimized Computation Offloading Performance in Virtual Edge Computing Systems via Deep Reinforcement Learning

Deep Learning in Mobile and Wireless Networking: A Survey

Adaptive Federated Learning in Resource Constrained Edge Computing Systems

Attention, Learn to Solve Routing Problems!

Deep Auxiliary Learning for Visual Localization and Odometry

Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis

A DIRT-T Approach to Unsupervised Domain Adaptation

Stronger generalization bounds for deep nets via a compression approach

UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks

IDEEA: training-free Input-Dependent stEEring via Activation cluster matching

Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

DeepSign: Deep Learning for Automatic Malware Signature Generation and Classification

Advances in Variational Inference

Certifying Some Distributional Robustness with Principled Adversarial Training

Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives

Real-Time Execution of Action Chunking Flow Policies

Lipschitz Continuity in Model-based Reinforcement Learning

End-to-end Driving via Conditional Imitation Learning

Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention

EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification