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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27,001 to 27,060 of 33,131

TROPT: An Open Framework for Unifying and Advancing Discrete Text Optimization
Matan Ben-Tov, Mahmood Sharif
cs.LGcs.CRarXiv:2606.23496v12026
Spectrally approximating large graphs with smaller graphs
Andreas Loukas, Pierre Vandergheynst
cs.LGcs.DSstat.MLarXiv:1802.07510v12018
HarmoCore: Functional Latent Diffusion for Sparse Reconstruction of Oscillatory Wave Fields
Lihao Chen, Xinyu Zhang, Panqi Chen +4
cs.LGcs.CEarXiv:2609.00679v12026
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles
Kashyap Chitta, Jose M. Alvarez, Adam Lesnikowski
cs.CVcs.LGstat.MLarXiv:1811.03575v32018
Diffusion Model Alignment Using Direct Preference Optimization
Bram Wallace, Meihua Dang, Rafael Rafailov +7
cs.CVcs.AIcs.GRarXiv:2311.12908v12023
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups
Paul Rolland, Jonathan Scarlett, Ilija Bogunovic +1
cs.LGstat.MLarXiv:1802.07028v22018
VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking
Limin Wang, Bingkun Huang, Zhiyu Zhao +5
cs.CVcs.LGarXiv:2303.16727v22023
MMErroR: A Benchmark for Erroneous Reasoning in Vision-Language Models
Yang Shi, Yifeng Xie, Minzhe Guo +6
cs.CVcs.AIcs.LGarXiv:2601.03331v22026
Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks
Amol Kapoor, Xue Ben, Luyang Liu +4
cs.LGcs.SIarXiv:2007.03113v12020
Comparing Retrieval Methods for Academic Advisor Discovery: A Six-Method Study of 768 CS Faculty Profiles Across 9 US Universities
Biraj Subedi
cs.IRcs.LGarXiv:2609.03901v12026
Cordial Learning: Distributed Training with Correlated Data
Sarah Shitrit, Ilai Bistritz
cs.LGcs.AIarXiv:2610.03330v12026
SparseMAP: Differentiable Sparse Structured Inference
Vlad Niculae, André F. T. Martins, Mathieu Blondel +1
stat.MLcs.CLcs.LGarXiv:1802.04223v22018
ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error Resilience for Energy Efficient Deep Neural Network Accelerators
Jeff Zhang, Kartheek Rangineni, Zahra Ghodsi +1
cs.NEcs.ARcs.LGarXiv:1802.03806v22018
Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process
Guy Blanc, Neha Gupta, Gregory Valiant +1
cs.LGstat.MLarXiv:1904.09080v22019
Rapid Locomotion via Reinforcement Learning
Gabriel B Margolis, Ge Yang, Kartik Paigwar +2
cs.ROcs.AIcs.LGarXiv:2205.02824v12022
The choice of scaling technique matters for classification performance
Lucas B. V. de Amorim, George D. C. Cavalcanti, Rafael M. O. Cruz
cs.LGarXiv:2212.12343v12022
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan +1
cs.LGcond-mat.dis-nnq-bio.NCarXiv:1503.03585v82015
ReToken: One Token to Improve Vision-Language Models for Visual Retrieval
Yao Xiao, Reuben Tan, Zhen Zhu +3
cs.CVcs.AIcs.LGarXiv:2607.28627v12026
Rethinking Optimal Transport in Offline Reinforcement Learning
Arip Asadulaev, Rostislav Korst, Alexander Korotin +3
cs.LGarXiv:2410.14069v12024
EdiText: Controllable Coarse-to-Fine Text Editing with Diffusion Language Models
Che Hyun Lee, Heeseung Kim, Jiheum Yeom +1
cs.CLcs.LGarXiv:2502.19765v22025
ValueGraph: Value-Signal Guided Graph Pre-training for Contextualized User Representation
Yitong Han, Wei Gao, Yi Zhao +3
cs.CLcs.AIcs.LGarXiv:2609.00057v12026
IQ-Learn: Inverse soft-Q Learning for Imitation
Divyansh Garg, Shuvam Chakraborty, Chris Cundy +3
cs.LGcs.AIarXiv:2106.12142v42021
Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design
Chenyu Wang, Masatoshi Uehara, Yichun He +7
cs.LGcs.AIarXiv:2410.13643v22024
Kernel Singular Value Decomposition with Extension to Multiple Data Sources
Xinjie Zeng, Qinghua Tao, Johan Suykens
cs.LGarXiv:2610.03216v12026
Object Contour Detection with a Fully Convolutional Encoder-Decoder Network
Jimei Yang, Brian Price, Scott Cohen +2
cs.CVcs.LGarXiv:1603.04530v12016
HyperFuse: Fast Self-Supervised Node Embeddings for Attributed Hypergraphs
Megha P, Harshit Kumar, Srajan Agarwal +3
cs.LGarXiv:2610.03211v12026
Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threads
John Thorpe, Yifan Qiao, Jonathan Eyolfson +8
cs.DCcs.LGarXiv:2105.11118v22021
Dynamics of Deep Neural Networks and Neural Tangent Hierarchy
Jiaoyang Huang, Horng-Tzer Yau
cs.LGstat.MLarXiv:1909.08156v12019
WxFM-XL: Adapting Univariate Foundation Models to Multi-Station Weather Forecasting
Xiao Wang, Changjian Chen, Zhuo Tang +3
cs.LGarXiv:2610.10057v12026
CityDeploy-Bench: Benchmarking Physics-Grounded Spatial Set Planning for Multi-Transmitter Network Deployment
Chenyang Yuan, Xiaoyuan Cheng
cs.LGarXiv:2610.11065v12026
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Runhua Xu, Nathalie Baracaldo, James Joshi
cs.LGcs.AIcs.CRarXiv:2108.04417v22021
Impossibility Theorems for Feature Attribution
Blair Bilodeau, Natasha Jaques, Pang Wei Koh +1
cs.LGcs.AIarXiv:2212.11870v32022
Contrastive Multi-View Representation Learning on Graphs
Kaveh Hassani, Amir Hosein Khasahmadi
cs.LGstat.MLarXiv:2006.05582v12020
MUGEN: Generating Unlearnable Graph Examples for Multiple Learning Tasks
Ziyan Liu, Chengshuai Zhao, Huan Liu
cs.LGarXiv:2609.00696v22026
Robust Semantic Communications with Masked VQ-VAE Enabled Codebook
Qiyu Hu, Guangyi Zhang, Zhijin Qin +3
eess.SPcs.ITcs.LGarXiv:2206.04011v22022
Meta Flow Maps enable scalable reward alignment
Peter Potaptchik, Adhi Saravanan, Abbas Mammadov +3
stat.MLcs.LGarXiv:2601.14430v22026
Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening
Andre He, Daniel Fried, Sean Welleck
cs.LGarXiv:2506.02355v22025
ASGO: Adaptive Structured Gradient Optimization
Kang An, Yuxing Liu, Rui Pan +4
cs.LGmath.OCarXiv:2503.20762v32025
Multiple Instance Learning Networks for Fine-Grained Sentiment Analysis
Stefanos Angelidis, Mirella Lapata
cs.CLcs.IRcs.LGarXiv:1711.09645v22017
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh +4
cs.LGarXiv:2401.18079v62024
Meta-SGD: Learning to Learn Quickly for Few-Shot Learning
Zhenguo Li, Fengwei Zhou, Fei Chen +1
cs.LGarXiv:1707.09835v22017
'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participants
Shivani Kapania, William Agnew, Motahhare Eslami +2
cs.HCcs.CLcs.LGarXiv:2409.19430v12024
Learning Robust Visual-Semantic Embeddings
Yao-Hung Hubert Tsai, Liang-Kang Huang, Ruslan Salakhutdinov
cs.CVcs.CLcs.LGarXiv:1703.05908v22017
Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation
Zihan Su, Hongyang Wei, Kangrui Cen +4
cs.CVcs.LGarXiv:2601.21406v32026
Deep supervised learning using local errors
Hesham Mostafa, Vishwajith Ramesh, Gert Cauwenberghs
cs.NEcs.LGstat.MLarXiv:1711.06756v12017
Provable approximation properties for deep neural networks
Uri Shaham, Alexander Cloninger, Ronald R. Coifman
stat.MLcs.LGcs.NEarXiv:1509.07385v32015
An Introduction to Probabilistic Programming
Jan-Willem van de Meent, Brooks Paige, Hongseok Yang +1
stat.MLcs.AIcs.LGarXiv:1809.10756v22018
From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare
Ming Li, Pengcheng Xu, Junjie Hu +2
cs.LGcs.AIarXiv:2409.09727v22024
Sample complexity of variance-reduced policy gradient: weaker assumptions and lower bounds
Gabor Paczolay, Matteo Papini, Alberto Maria Metelli +2
cs.LGarXiv:2610.03165v12026
Cautious NMPC with Gaussian Process Dynamics for Autonomous Miniature Race Cars
Lukas Hewing, Alexander Liniger, Melanie N. Zeilinger
eess.SYcs.LGcs.SYarXiv:1711.06586v22017
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes
Matteo Turchetta, Felix Berkenkamp, Andreas Krause
cs.LGcs.AIcs.ROarXiv:1606.04753v22016
Hindsight policy gradients
Paulo Rauber, Avinash Ummadisingu, Filipe Mutz +1
cs.LGcs.AIcs.NEarXiv:1711.06006v32017
Does Physics Live in the Activations? Localizing Physical Quantities in Video Diffusion Models
Jonas Kneifl, Jakub Skalski, Bartłomiej Twardowski +1
cs.CVcs.LGarXiv:2610.03154v12026
Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning
Sakrapee Paisitkriangkrai, Chunhua Shen, Anton van den Hengel
cs.CVcs.LGarXiv:1409.5209v32014
A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs
Zequn Sun, Qingheng Zhang, Wei Hu +4
cs.CLcs.AIcs.DBarXiv:2003.07743v22020
On the Power of Differentiable Learning versus PAC and SQ Learning
Emmanuel Abbe, Pritish Kamath, Eran Malach +2
cs.LGstat.MLarXiv:2108.04190v22021
Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification
Eric Zhao, Pranjal Awasthi, Sreenivas Gollapudi
cs.LGcs.AIarXiv:2502.01839v22025
The T05 System for The VoiceMOS Challenge 2024: Transfer Learning from Deep Image Classifier to Naturalness MOS Prediction of High-Quality Synthetic Speech
Kaito Baba, Wataru Nakata, Yuki Saito +1
cs.SDcs.AIcs.LGarXiv:2409.09305v12024
Methods for Interpreting and Understanding Deep Neural Networks
Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
cs.LGstat.MLarXiv:1706.07979v12017
Robust Industrial Cyber Physical Classification Using Neuromorphic Temporal Embeddings and Hybrid SNN XGBoost Under Machine Unlearning Attacks
Ammar Kamoona, Sajad Koushkbaghi, Mahdi Jalili +2
cs.LGcs.CRcs.NEarXiv:2609.09564v12026

Machine Learning

TROPT: An Open Framework for Unifying and Advancing Discrete Text Optimization

Spectrally approximating large graphs with smaller graphs

HarmoCore: Functional Latent Diffusion for Sparse Reconstruction of Oscillatory Wave Fields

Large-Scale Visual Active Learning with Deep Probabilistic Ensembles

Diffusion Model Alignment Using Direct Preference Optimization

High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups

VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking

MMErroR: A Benchmark for Erroneous Reasoning in Vision-Language Models

Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks

Comparing Retrieval Methods for Academic Advisor Discovery: A Six-Method Study of 768 CS Faculty Profiles Across 9 US Universities

Cordial Learning: Distributed Training with Correlated Data

SparseMAP: Differentiable Sparse Structured Inference

ThUnderVolt: Enabling Aggressive Voltage Underscaling and Timing Error Resilience for Energy Efficient Deep Neural Network Accelerators

Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process

Rapid Locomotion via Reinforcement Learning

The choice of scaling technique matters for classification performance

Deep Unsupervised Learning using Nonequilibrium Thermodynamics

ReToken: One Token to Improve Vision-Language Models for Visual Retrieval

Rethinking Optimal Transport in Offline Reinforcement Learning

EdiText: Controllable Coarse-to-Fine Text Editing with Diffusion Language Models

ValueGraph: Value-Signal Guided Graph Pre-training for Contextualized User Representation

IQ-Learn: Inverse soft-Q Learning for Imitation

Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design

Kernel Singular Value Decomposition with Extension to Multiple Data Sources

Object Contour Detection with a Fully Convolutional Encoder-Decoder Network

HyperFuse: Fast Self-Supervised Node Embeddings for Attributed Hypergraphs

Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threads

Dynamics of Deep Neural Networks and Neural Tangent Hierarchy

WxFM-XL: Adapting Univariate Foundation Models to Multi-Station Weather Forecasting

CityDeploy-Bench: Benchmarking Physics-Grounded Spatial Set Planning for Multi-Transmitter Network Deployment

Privacy-Preserving Machine Learning: Methods, Challenges and Directions

Impossibility Theorems for Feature Attribution

Contrastive Multi-View Representation Learning on Graphs

MUGEN: Generating Unlearnable Graph Examples for Multiple Learning Tasks

Robust Semantic Communications with Masked VQ-VAE Enabled Codebook

Meta Flow Maps enable scalable reward alignment

Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening

ASGO: Adaptive Structured Gradient Optimization

Multiple Instance Learning Networks for Fine-Grained Sentiment Analysis

KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization

Meta-SGD: Learning to Learn Quickly for Few-Shot Learning

'Simulacrum of Stories': Examining Large Language Models as Qualitative Research Participants

Learning Robust Visual-Semantic Embeddings

Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation

Deep supervised learning using local errors

Provable approximation properties for deep neural networks

An Introduction to Probabilistic Programming

From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare

Sample complexity of variance-reduced policy gradient: weaker assumptions and lower bounds

Cautious NMPC with Gaussian Process Dynamics for Autonomous Miniature Race Cars

Safe Exploration in Finite Markov Decision Processes with Gaussian Processes

Hindsight policy gradients

Does Physics Live in the Activations? Localizing Physical Quantities in Video Diffusion Models

Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning

A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs

On the Power of Differentiable Learning versus PAC and SQ Learning

Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification

The T05 System for The VoiceMOS Challenge 2024: Transfer Learning from Deep Image Classifier to Naturalness MOS Prediction of High-Quality Synthetic Speech

Methods for Interpreting and Understanding Deep Neural Networks

Robust Industrial Cyber Physical Classification Using Neuromorphic Temporal Embeddings and Hybrid SNN XGBoost Under Machine Unlearning Attacks