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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2,761 to 2,820 of 20,108

Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani +5
cs.LGcs.AIstat.MLarXiv:2003.06016v22020
Document Understanding Dataset and Evaluation (DUDE)
Jordy Van Landeghem, Rubén Tito, Łukasz Borchmann +10
cs.CVcs.CLcs.LGarXiv:2305.08455v32023
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation
Yukai Liu, Rose Yu, Stephan Zheng +2
cs.LGstat.MLarXiv:1901.10946v32019
Equivariance Breaks the Learning Rate
Andrei Manolache, Mathias Niepert
cs.LGcs.AIarXiv:2609.08381v12026
Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors
Rico Jonschkowski, Divyam Rastogi, Oliver Brock
cs.LGcs.AIcs.ROarXiv:1805.11122v22018
ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale
William Won, Taekyung Heo, Saeed Rashidi +3
cs.DCcs.LGarXiv:2303.14006v12023
Bootstrapping Semantic Segmentation with Regional Contrast
Shikun Liu, Shuaifeng Zhi, Edward Johns +1
cs.CVcs.LGarXiv:2104.04465v42021
Supervised Pretraining Can Learn In-Context Reinforcement Learning
Jonathan N. Lee, Annie Xie, Aldo Pacchiano +4
cs.LGcs.AIarXiv:2306.14892v12023
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models
Yongshuo Zong, Ondrej Bohdal, Tingyang Yu +2
cs.LGarXiv:2402.02207v22024
A Measurement Study of LLM Inference Trade-offs Across Edge Continuum Hardware
Maysam Khatib, Moysis Symeonides, Demetris Trihinas +2
cs.DCcs.AIcs.LGarXiv:2609.08307v12026
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints
Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
cs.LGmath.DSphysics.comp-pharXiv:2010.13581v12020
Architectural Complexity Measures of Recurrent Neural Networks
Saizheng Zhang, Yuhuai Wu, Tong Che +4
cs.LGcs.NEarXiv:1602.08210v32016
FedCM: Federated Learning with Client-level Momentum
Jing Xu, Sen Wang, Liwei Wang +1
cs.LGarXiv:2106.10874v12021
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space
Nikolas Nüsken, Lorenz Richter
math.OCcs.LGmath.NAarXiv:2005.05409v22020
IPM-FM: A Foundation Model with Consensus Feature Selection for Industrial Process Monitoring
Liang Cao, Weide Liu, Yan Qin +3
cs.LGcs.AIarXiv:2609.08375v12026
Condensing Graphs via One-Step Gradient Matching
Wei Jin, Xianfeng Tang, Haoming Jiang +4
cs.LGcs.AIarXiv:2206.07746v32022
Learning Hidden Unit Contributions for Unsupervised Acoustic Model Adaptation
Pawel Swietojanski, Jinyu Li, Steve Renals
cs.CLcs.LGcs.SDarXiv:1601.02828v22016
Tarsier: Recipes for Training and Evaluating Large Video Description Models
Jiawei Wang, Liping Yuan, Yuchen Zhang +1
cs.CVcs.LGarXiv:2407.00634v22024
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach
Mao Ye, Bo Liu, Stephen Wright +2
cs.LGcs.AImath.OCarXiv:2209.08709v12022
Audio Super Resolution using Neural Networks
Volodymyr Kuleshov, S. Zayd Enam, Stefano Ermon
cs.SDcs.LGarXiv:1708.00853v12017
Neural Thompson Sampling
Weitong Zhang, Dongruo Zhou, Lihong Li +1
cs.LGstat.MLarXiv:2010.00827v22020
Semantic Human Matting
Quan Chen, Tiezheng Ge, Yanyu Xu +3
cs.CVcs.GRcs.LGarXiv:1809.01354v22018
Synergistic Fusion of Topological Structure and Temporal Semantics of Mobility for Urban Region Embedding
Namwoo Kim, Jeeyun Chang, Kanghoon Lee +1
cs.LGcs.AIarXiv:2609.08268v12026
On the Possibilities of AI-Generated Text Detection
Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu +3
cs.CLcs.AIcs.LGarXiv:2304.04736v32023
Visual Imitation Made Easy
Sarah Young, Dhiraj Gandhi, Shubham Tulsiani +3
cs.ROcs.CVcs.LGarXiv:2008.04899v12020
Vision-based Navigation with Language-based Assistance via Imitation Learning with Indirect Intervention
Khanh Nguyen, Debadeepta Dey, Chris Brockett +1
cs.LGcs.CLcs.CVarXiv:1812.04155v42018
Neural networks for option pricing and hedging: a literature review
Johannes Ruf, Weiguan Wang
q-fin.CPcs.LGq-fin.RMarXiv:1911.05620v22019
RenderFormer-V2: Neural Rendering with Heterogeneous Scene Primitives
Chong Zeng, Yue Dong, Pieter Peers +2
cs.CVcs.GRcs.LGarXiv:2609.05738v12026
Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search
Ali Yahya, Adrian Li, Mrinal Kalakrishnan +2
cs.LGcs.AIcs.ROarXiv:1610.00673v12016
Deep Generative Dual Memory Network for Continual Learning
Nitin Kamra, Umang Gupta, Yan Liu
cs.LGarXiv:1710.10368v22017
Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structure
Ke Liang, Yue Liu, Sihang Zhou +5
cs.AIcs.IRcs.LGarXiv:2211.10738v42022
Diffusion Models for Time Series Applications: A Survey
Lequan Lin, Zhengkun Li, Ruikun Li +2
cs.LGarXiv:2305.00624v12023
Active Semi-Supervised Learning Using Sampling Theory for Graph Signals
Akshay Gadde, Aamir Anis, Antonio Ortega
cs.LGstat.MLarXiv:1405.4324v12014
Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction
N. Benjamin Erichson, Michael Muehlebach, Michael W. Mahoney
physics.comp-phcs.LGarXiv:1905.10866v12019
Deep Learning for Wireless Communications
Tugba Erpek, Timothy J. O'Shea, Yalin E. Sagduyu +2
cs.NIcs.LGarXiv:2005.06068v12020
Online Multi-agent Reinforcement Learning for Decentralized Inverter-based Volt-VAR Control
Haotian Liu, Wenchuan Wu
eess.SYcs.LGcs.MAarXiv:2006.12841v22020
Video Generative Adversarial Networks: A Review
Nuha Aldausari, Arcot Sowmya, Nadine Marcus +1
cs.CVcs.LGeess.IVarXiv:2011.02250v12020
gDDIM: Generalized denoising diffusion implicit models
Qinsheng Zhang, Molei Tao, Yongxin Chen
cs.LGarXiv:2206.05564v22022
A Survey of Complex-Valued Neural Networks
Joshua Bassey, Lijun Qian, Xianfang Li
stat.MLcs.LGarXiv:2101.12249v12021
A Sociotechnical View of Algorithmic Fairness
Mateusz Dolata, Stefan Feuerriegel, Gerhard Schwabe
cs.CYcs.LGstat.MLarXiv:2110.09253v12021
Differentially Private Synthetic Medical Data Generation using Convolutional GANs
Amirsina Torfi, Edward A. Fox, Chandan K. Reddy
cs.LGcs.AIarXiv:2012.11774v12020
PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations
Moshe Eliasof, Eldad Haber, Eran Treister
cs.LGcs.CVcs.NEarXiv:2108.01938v22021
Invariant Information Bottleneck for Domain Generalization
Bo Li, Yifei Shen, Yezhen Wang +6
cs.LGstat.MLarXiv:2106.06333v62021
Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates
Ilija Ilievski, Taimoor Akhtar, Jiashi Feng +1
cs.AIcs.LGstat.MLarXiv:1607.08316v22016
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning
Justin Fu, John D. Co-Reyes, Sergey Levine
cs.LGarXiv:1703.01260v22017
LLM Layers Immediately Correct Each Other
Arjun Patrawala, Jiahai Feng, Erik Jones +1
cs.CLcs.LGarXiv:2609.07876v12026
Transformer-Based Language Models for Software Vulnerability Detection
Chandra Thapa, Seung Ick Jang, Muhammad Ejaz Ahmed +3
cs.CRcs.AIcs.LGarXiv:2204.03214v22022
KBBQ: A Predictive Noise Law and the Limits of Spectrum Flattening in FP4 Quantization
Lexington Whalen, Yuki Ito, Ryo Sakamoto
cs.LGcs.AIarXiv:2609.08135v12026
A survey on domain adaptation theory: learning bounds and theoretical guarantees
Ievgen Redko, Emilie Morvant, Amaury Habrard +2
cs.LGstat.MLarXiv:2004.11829v62020
Sparse Data Augmentation for Optimization with Provable Guarantees
Behrooz Tahmasebi, Melanie Weber
cs.LGcs.AImath.OCarXiv:2609.08133v12026
Systematic Ensemble Model Selection Approach for Educational Data Mining
MohammadNoor Injadat, Abdallah Moubayed, Ali Bou Nassif +1
cs.CYcs.LGarXiv:2005.06647v12020
DISEIL: Demonstration Distillation for Sample-Efficient Imitation Learning
Suyog Khanal, Arun Kumar A, Santu Rana
cs.ROcs.AIcs.LGarXiv:2609.08123v12026
Hidden in Plain Sight: The Overlooked Significance of Canonical Elements for Extreme LLM Sparsity
Hyeondo Jang, Kwanhee Lee, Dongyeop Lee +1
cs.LGarXiv:2609.06557v12026
Hybrid-FL for Wireless Networks: Cooperative Learning Mechanism Using Non-IID Data
Naoya Yoshida, Takayuki Nishio, Masahiro Morikura +2
cs.LGcs.DCstat.MLarXiv:1905.07210v32019
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs
Harini Suresh, Steven R. Gomez, Kevin K. Nam +1
cs.HCcs.CYcs.LGarXiv:2101.09824v12021
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning
Felix Sattler, Tim Korjakow, Roman Rischke +1
cs.LGcs.DCstat.MLarXiv:2102.02514v12021
Balanced Policy Evaluation and Learning
Nathan Kallus
stat.MLcs.LGmath.OCarXiv:1705.07384v22017
Foundation Models for Generalizable Semantic and Goal-Oriented Communication
Boliang Liu, Wint Yi Poe, Riccardo Trivisonno +1
cs.LGcs.AIcs.ROarXiv:2609.07853v12026
Communication-Computation Trade-Off in Resource-Constrained Edge Inference
Jiawei Shao, Jun Zhang
cs.LGeess.SPstat.MLarXiv:2006.02166v22020
A Conformal Prediction Approach to Explore Functional Data
Jing Lei, Alessandro Rinaldo, Larry Wasserman
stat.MLcs.LGarXiv:1302.6452v12013

Machine Learning

Invariant Causal Prediction for Block MDPs

Document Understanding Dataset and Evaluation (DUDE)

NAOMI: Non-Autoregressive Multiresolution Sequence Imputation

Equivariance Breaks the Learning Rate

Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors

ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale

Bootstrapping Semantic Segmentation with Regional Contrast

Supervised Pretraining Can Learn In-Context Reinforcement Learning

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models

A Measurement Study of LLM Inference Trade-offs Across Edge Continuum Hardware

Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints

Architectural Complexity Measures of Recurrent Neural Networks

FedCM: Federated Learning with Client-level Momentum

Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space

IPM-FM: A Foundation Model with Consensus Feature Selection for Industrial Process Monitoring

Condensing Graphs via One-Step Gradient Matching

Learning Hidden Unit Contributions for Unsupervised Acoustic Model Adaptation

Tarsier: Recipes for Training and Evaluating Large Video Description Models

BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach

Audio Super Resolution using Neural Networks

Neural Thompson Sampling

Semantic Human Matting

Synergistic Fusion of Topological Structure and Temporal Semantics of Mobility for Urban Region Embedding

On the Possibilities of AI-Generated Text Detection

Visual Imitation Made Easy

Vision-based Navigation with Language-based Assistance via Imitation Learning with Indirect Intervention

Neural networks for option pricing and hedging: a literature review

RenderFormer-V2: Neural Rendering with Heterogeneous Scene Primitives

Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search

Deep Generative Dual Memory Network for Continual Learning

Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structure

Diffusion Models for Time Series Applications: A Survey

Active Semi-Supervised Learning Using Sampling Theory for Graph Signals

Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction

Deep Learning for Wireless Communications

Online Multi-agent Reinforcement Learning for Decentralized Inverter-based Volt-VAR Control

Video Generative Adversarial Networks: A Review

gDDIM: Generalized denoising diffusion implicit models

A Survey of Complex-Valued Neural Networks

A Sociotechnical View of Algorithmic Fairness

Differentially Private Synthetic Medical Data Generation using Convolutional GANs

PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations

Invariant Information Bottleneck for Domain Generalization

Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates

EX2: Exploration with Exemplar Models for Deep Reinforcement Learning

LLM Layers Immediately Correct Each Other

Transformer-Based Language Models for Software Vulnerability Detection

KBBQ: A Predictive Noise Law and the Limits of Spectrum Flattening in FP4 Quantization

A survey on domain adaptation theory: learning bounds and theoretical guarantees

Sparse Data Augmentation for Optimization with Provable Guarantees

Systematic Ensemble Model Selection Approach for Educational Data Mining

DISEIL: Demonstration Distillation for Sample-Efficient Imitation Learning

Hidden in Plain Sight: The Overlooked Significance of Canonical Elements for Extreme LLM Sparsity

Hybrid-FL for Wireless Networks: Cooperative Learning Mechanism Using Non-IID Data

Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs

FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning

Balanced Policy Evaluation and Learning

Foundation Models for Generalizable Semantic and Goal-Oriented Communication

Communication-Computation Trade-Off in Resource-Constrained Edge Inference

A Conformal Prediction Approach to Explore Functional Data