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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10,261 to 10,320 of 20,153

Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence
Nicolas Loizou, Sharan Vaswani, Issam Laradji +1
math.OCcs.LGstat.MLarXiv:2002.10542v32020
Disentangled Representation Learning
Xin Wang, Hong Chen, Si'ao Tang +2
cs.LGcs.AIarXiv:2211.11695v42022
An Introduction to Vision-Language Modeling
Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay +38
cs.LGarXiv:2405.17247v12024
A Bayesian Data Augmentation Approach for Learning Deep Models
Toan Tran, Trung Pham, Gustavo Carneiro +2
cs.CVcs.LGarXiv:1710.10564v12017
Deep Reinforcement Learning For Sequence to Sequence Models
Yaser Keneshloo, Tian Shi, Naren Ramakrishnan +1
cs.LGstat.MLarXiv:1805.09461v42018
The State of the Art in Integrating Machine Learning into Visual Analytics
A. Endert, W. Ribarsky, C. Turkay +4
stat.MLcs.HCcs.LGarXiv:1802.07954v12018
Wav-KAN: Wavelet Kolmogorov-Arnold Networks
Zavareh Bozorgasl, Hao Chen
cs.LGcs.AIeess.SParXiv:2405.12832v22024
Driving Policy Transfer via Modularity and Abstraction
Matthias Müller, Alexey Dosovitskiy, Bernard Ghanem +1
cs.ROcs.CVcs.LGarXiv:1804.09364v32018
Relational Deep Reinforcement Learning
Vinicius Zambaldi, David Raposo, Adam Santoro +13
cs.LGstat.MLarXiv:1806.01830v22018
Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning
Yingdong Hu, Fanqi Lin, Tong Zhang +2
cs.ROcs.AIcs.CLarXiv:2311.17842v22023
Benchmarking large language models for biomedical natural language processing applications and recommendations
Qingyu Chen, Yan Hu, Xueqing Peng +18
cs.CLcs.AIcs.IRarXiv:2305.16326v52023
Semi-Stochastic Gradient Descent Methods
Jakub Konečný, Peter Richtárik
stat.MLcs.LGmath.NAarXiv:1312.1666v22013
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks
Khemraj Shukla, Juan Diego Toscano, Zhicheng Wang +2
cs.LGphysics.comp-pharXiv:2406.02917v12024
End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
Yansong Gao, Minki Kim, Sharif Abuadbba +6
cs.CRcs.DCcs.LGarXiv:2003.13376v22020
TenSEAL: A Library for Encrypted Tensor Operations Using Homomorphic Encryption
Ayoub Benaissa, Bilal Retiat, Bogdan Cebere +1
cs.CRcs.LGarXiv:2104.03152v22021
Simple And Efficient Architecture Search for Convolutional Neural Networks
Thomas Elsken, Jan-Hendrik Metzen, Frank Hutter
stat.MLcs.AIcs.LGarXiv:1711.04528v12017
CodeGen2: Lessons for Training LLMs on Programming and Natural Languages
Erik Nijkamp, Hiroaki Hayashi, Caiming Xiong +2
cs.LGarXiv:2305.02309v22023
QUOTIENT: Two-Party Secure Neural Network Training and Prediction
Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner +1
cs.CRcs.LGarXiv:1907.03372v12019
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection
Guansong Pang, Longbing Cao, Ling Chen +1
cs.LGcs.AIcs.DBarXiv:1806.04808v12018
Fooling Neural Network Interpretations via Adversarial Model Manipulation
Juyeon Heo, Sunghwan Joo, Taesup Moon
cs.LGcs.AIcs.CVarXiv:1902.02041v32019
ReLoRA: High-Rank Training Through Low-Rank Updates
Vladislav Lialin, Namrata Shivagunde, Sherin Muckatira +1
cs.CLcs.LGarXiv:2307.05695v42023
Multi-Task Reinforcement Learning with Soft Modularization
Ruihan Yang, Huazhe Xu, Yi Wu +1
cs.LGcs.AIcs.ROarXiv:2003.13661v22020
Benchmarking Self-Supervised Learning on Diverse Pathology Datasets
Mingu Kang, Heon Song, Seonwook Park +2
cs.CVcs.LGarXiv:2212.04690v22022
Deep Learning-Based Gait Recognition Using Smartphones in the Wild
Qin Zou, Yanling Wang, Qian Wang +2
cs.LGeess.SPstat.MLarXiv:1811.00338v32018
RvS: What is Essential for Offline RL via Supervised Learning?
Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov +1
cs.LGcs.AIstat.MLarXiv:2112.10751v22021
Enhancing Robustness of Machine Learning Systems via Data Transformations
Arjun Nitin Bhagoji, Daniel Cullina, Chawin Sitawarin +1
cs.CRcs.LGarXiv:1704.02654v42017
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Enyan Dai, Tianxiang Zhao, Huaisheng Zhu +5
cs.LGcs.CRarXiv:2204.08570v22022
PySINDy: A comprehensive Python package for robust sparse system identification
Alan A. Kaptanoglu, Brian M. de Silva, Urban Fasel +9
eess.SYcs.LGphysics.flu-dynarXiv:2111.08481v22021
A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research
Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi +1
cs.IRcs.LGcs.NEarXiv:1911.07698v32019
BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment Analysis
Wei Li, Wei Shao, Shaoxiong Ji +1
cs.CLcs.LGarXiv:2006.00492v32020
Automatic Curriculum Learning For Deep RL: A Short Survey
Rémy Portelas, Cédric Colas, Lilian Weng +2
cs.LGcs.AIstat.MLarXiv:2003.04664v22020
Orthogonal Statistical Learning
Dylan J. Foster, Vasilis Syrgkanis
math.STcs.LGecon.EMarXiv:1901.09036v42019
When Does a Classifier Help an LLM? Classifier-Guided Prompting and Hybrid Classifier-LLM Models for Credit-Default Prediction
Rishi Datta, Lavanya Prahallad
cs.CLcs.LGarXiv:2608.30086v12026
Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network
Sijin Li, Zhi-Qiang Liu, Antoni B. Chan
cs.CVcs.LGcs.NEarXiv:1406.3474v12014
Word Embeddings: A Survey
Felipe Almeida, Geraldo Xexéo
cs.CLcs.LGstat.MLarXiv:1901.09069v22019
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong
Warren He, James Wei, Xinyun Chen +2
cs.LGarXiv:1706.04701v12017
Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment
Lingxiao Kong, Steffen Staab, Cong Yang +2
cs.CLcs.LGcs.NEarXiv:2608.29978v12026
Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences
Hongyuan Mei, Mohit Bansal, Matthew R. Walter
cs.CLcs.AIcs.LGarXiv:1506.04089v42015
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization
Daniel Jakubovitz, Raja Giryes
cs.LGcs.CRcs.CVarXiv:1803.08680v42018
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
Robert L. Logan, Ivana Balažević, Eric Wallace +3
cs.CLcs.LGarXiv:2106.13353v22021
Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications
Moming Duan, Duo Liu, Xianzhang Chen +4
cs.LGcs.DCstat.MLarXiv:1907.01132v22019
Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
Peng Chen, Yingying Zhang, Yunyao Cheng +5
cs.LGarXiv:2402.05956v52024
LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation
Jianwei Yang, Anitha Kannan, Dhruv Batra +1
cs.CVcs.LGarXiv:1703.01560v32017
Optimal Algorithms for Testing Closeness of Discrete Distributions
Siu-On Chan, Ilias Diakonikolas, Gregory Valiant +1
cs.DScs.ITcs.LGarXiv:1308.3946v12013
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations
Abbas Sadat, Sergio Casas, Mengye Ren +3
cs.ROcs.AIcs.CVarXiv:2008.05930v12020
Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
Sushravya Raghunath, Alvaro E. Ulloa Cerna, Linyuan Jing +12
q-bio.QMcs.LGstat.MLarXiv:1904.07032v32019
Fast Supervised Discrete Hashing
Jie Gui, Tongliang Liu, Zhenan Sun +2
cs.LGstat.MLarXiv:1904.03556v12019
A Deep Reinforcement Learning Chatbot
Iulian V. Serban, Chinnadhurai Sankar, Mathieu Germain +15
cs.CLcs.AIcs.LGarXiv:1709.02349v22017
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Weizhi Ma, Min Zhang, Yue Cao +6
cs.IRcs.AIcs.LGarXiv:1903.03714v12019
When Safety Speaks a Language: A Mechanistic Analysis of Safety-Language Identity Entanglement in LLMs
Apoorva Upadhyaya, Sandipan Sikdar
cs.CLcs.LGarXiv:2608.29936v12026
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
Ziwei Fan, Zhiwei Liu, Jiawei Zhang +3
cs.IRcs.AIcs.LGarXiv:2108.06625v22021
Compression-Aware Abstention: Teaching LLMs to Refuse When KV-Compression Masks Remove Answer Evidence
Mohammadali Khodabandehlou, Bhaskar Krishnamachari
cs.CLcs.LGarXiv:2608.29934v12026
Re-Identification with Consistent Attentive Siamese Networks
Meng Zheng, Srikrishna Karanam, Ziyan Wu +1
cs.CVcs.LGarXiv:1811.07487v42018
MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification
Chang Wei Tan, Angus Dempster, Christoph Bergmeir +1
cs.LGstat.MLarXiv:2102.00457v42021
FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface
Ravikiran Mane, Effie Chew, Karen Chua +5
cs.OHcs.AIcs.LGarXiv:2104.01233v12021
Augmenting Organizational Decision-Making with Deep Learning Algorithms: Principles, Promises, and Challenges
Yash Raj Shrestha, Vaibhav Krishna, Georg von Krogh
cs.LGarXiv:2011.02834v12020
Toward Optimal Feature Selection in Naive Bayes for Text Categorization
Bo Tang, Steven Kay, Haibo He
stat.MLcs.CLcs.IRarXiv:1602.02850v12016
Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning
Georgios Papoudakis, Filippos Christianos, Arrasy Rahman +1
cs.LGcs.AIcs.MAarXiv:1906.04737v12019
IDNet: Smartphone-based Gait Recognition with Convolutional Neural Networks
Matteo Gadaleta, Michele Rossi
cs.CVcs.LGarXiv:1606.03238v32016
Influence-Directed Distillation: Solving the Diversity Bottleneck in Sampled-Token On-Policy Distillation
Run Yang, Runpeng Dai, Jie Sun +5
cs.CLcs.LGarXiv:2608.29846v12026

Machine Learning

Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence

Disentangled Representation Learning

An Introduction to Vision-Language Modeling

A Bayesian Data Augmentation Approach for Learning Deep Models

Deep Reinforcement Learning For Sequence to Sequence Models

The State of the Art in Integrating Machine Learning into Visual Analytics

Wav-KAN: Wavelet Kolmogorov-Arnold Networks

Driving Policy Transfer via Modularity and Abstraction

Relational Deep Reinforcement Learning

Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning

Benchmarking large language models for biomedical natural language processing applications and recommendations

Semi-Stochastic Gradient Descent Methods

A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks

End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things

TenSEAL: A Library for Encrypted Tensor Operations Using Homomorphic Encryption

Simple And Efficient Architecture Search for Convolutional Neural Networks

CodeGen2: Lessons for Training LLMs on Programming and Natural Languages

QUOTIENT: Two-Party Secure Neural Network Training and Prediction

Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection

Fooling Neural Network Interpretations via Adversarial Model Manipulation

ReLoRA: High-Rank Training Through Low-Rank Updates

Multi-Task Reinforcement Learning with Soft Modularization

Benchmarking Self-Supervised Learning on Diverse Pathology Datasets

Deep Learning-Based Gait Recognition Using Smartphones in the Wild

RvS: What is Essential for Offline RL via Supervised Learning?

Enhancing Robustness of Machine Learning Systems via Data Transformations

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability

PySINDy: A comprehensive Python package for robust sparse system identification

A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research

BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment Analysis

Automatic Curriculum Learning For Deep RL: A Short Survey

Orthogonal Statistical Learning

When Does a Classifier Help an LLM? Classifier-Guided Prompting and Hybrid Classifier-LLM Models for Credit-Default Prediction

Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network

Word Embeddings: A Survey

Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong

Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment

Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences

Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization

Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models

Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications

Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting

LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation

Optimal Algorithms for Testing Closeness of Discrete Distributions

Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations

Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data

Fast Supervised Discrete Hashing

A Deep Reinforcement Learning Chatbot

Jointly Learning Explainable Rules for Recommendation with Knowledge Graph

When Safety Speaks a Language: A Mechanistic Analysis of Safety-Language Identity Entanglement in LLMs

Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

Compression-Aware Abstention: Teaching LLMs to Refuse When KV-Compression Masks Remove Answer Evidence

Re-Identification with Consistent Attentive Siamese Networks

MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification

FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface

Augmenting Organizational Decision-Making with Deep Learning Algorithms: Principles, Promises, and Challenges

Toward Optimal Feature Selection in Naive Bayes for Text Categorization

Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning

IDNet: Smartphone-based Gait Recognition with Convolutional Neural Networks

Influence-Directed Distillation: Solving the Diversity Bottleneck in Sampled-Token On-Policy Distillation