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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10,021 to 10,080 of 19,954

Implicit Semantic Data Augmentation for Deep Networks
Yulin Wang, Xuran Pan, Shiji Song +3
cs.CVcs.LGstat.MLarXiv:1909.12220v52019
Federated Learning for Ultra-Reliable Low-Latency V2V Communications
Sumudu Samarakoon, Mehdi Bennis, Walid Saad +1
cs.NIcs.LGstat.MLarXiv:1805.09253v12018
Quantum circuit architecture search for variational quantum algorithms
Yuxuan Du, Tao Huang, Shan You +2
quant-phcs.LGarXiv:2010.10217v32020
DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality
Ankur Handa, Arthur Allshire, Viktor Makoviychuk +11
cs.ROcs.LGarXiv:2210.13702v22022
Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges
Enrique Mármol Campos, Pablo Fernández Saura, Aurora González-Vidal +4
cs.LGcs.CRcs.NIarXiv:2108.00974v12021
Communication Algorithms via Deep Learning
Hyeji Kim, Yihan Jiang, Ranvir Rana +3
stat.MLcs.LGarXiv:1805.09317v12018
Clustering as Approximation by Constrained Projectors: Theory and Guarantees
Angshul Majumdar
cs.AIcs.LGarXiv:2608.29102v12026
Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey
Tianxu Li, Kun Zhu, Nguyen Cong Luong +4
cs.AIcs.LGcs.MAarXiv:2110.13484v32021
Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods
Yuji Cao, Huan Zhao, Yuheng Cheng +7
cs.LGcs.AIcs.CLarXiv:2404.00282v32024
Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges
Gabrielle Ras, Marcel van Gerven, Pim Haselager
cs.AIcs.LGstat.MLarXiv:1803.07517v22018
Ceiling-Clipped Acceptance Histograms Indicate Stranded Speed-up in Block-Diffusion Speculative Decoding
Ephrem Wu
cs.CLcs.LGarXiv:2608.30427v12026
Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors
Claudionor N. Coelho, Aki Kuusela, Shan Li +7
physics.ins-detcs.LGeess.IVarXiv:2006.10159v32020
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen +4
cs.LGcs.AIcs.CLarXiv:2310.06117v22023
Leakage and the Reproducibility Crisis in ML-based Science
Sayash Kapoor, Arvind Narayanan
cs.LGcs.AIstat.MEarXiv:2207.07048v12022
On the Origin of Deep Learning
Haohan Wang, Bhiksha Raj
cs.LGcs.NEstat.MLarXiv:1702.07800v42017
StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text
Roberto Henschel, Levon Khachatryan, Hayk Poghosyan +5
cs.CVcs.AIcs.CLarXiv:2403.14773v22024
RuleMatrix: Visualizing and Understanding Classifiers with Rules
Yao Ming, Huamin Qu, Enrico Bertini
cs.LGcs.AIcs.HCarXiv:1807.06228v12018
Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression
Aymeric Dieuleveut, Nicolas Flammarion, Francis Bach
math.OCcs.LGstat.MLarXiv:1602.05419v22016
Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control
Jacopo Panerati, Hehui Zheng, SiQi Zhou +3
cs.ROcs.LGarXiv:2103.02142v32021
ASlib: A Benchmark Library for Algorithm Selection
Bernd Bischl, Pascal Kerschke, Lars Kotthoff +8
cs.AIcs.LGarXiv:1506.02465v32015
Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs
Sungsoo Ray Hong, Jessica Hullman, Enrico Bertini
cs.HCcs.CYcs.LGarXiv:2004.11440v22020
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication
Felix Sattler, Simon Wiedemann, Klaus-Robert Müller +1
cs.LGcs.AIcs.DCarXiv:1805.08768v12018
Feature Engineering for Predictive Modeling using Reinforcement Learning
Udayan Khurana, Horst Samulowitz, Deepak Turaga
cs.AIcs.LGstat.MLarXiv:1709.07150v12017
Reward Model Ensembles Help Mitigate Overoptimization
Thomas Coste, Usman Anwar, Robert Kirk +1
cs.LGarXiv:2310.02743v22023
3D-LaneNet: End-to-End 3D Multiple Lane Detection
Noa Garnett, Rafi Cohen, Tomer Pe'er +2
cs.CVcs.LGcs.ROarXiv:1811.10203v32018
Fully Distributed GNE Algorithms for Multi-Robot Placement without Consensus on Multipliers
Shao-An Yin, Mingyi Hong, Nicola Elia
cs.LGcs.AIcs.GTarXiv:2608.29388v12026
Hyper-SAGNN: a self-attention based graph neural network for hypergraphs
Ruochi Zhang, Yuesong Zou, Jian Ma
cs.LGstat.MLarXiv:1911.02613v12019
Benchmarking Large Language Models for Automated Verilog RTL Code Generation
Shailja Thakur, Baleegh Ahmad, Zhenxing Fan +5
cs.PLcs.LGcs.SEarXiv:2212.11140v12022
Kathleen Remembers: Length-Invariant One-Shot Recall Without Attention
George Fountzoulas
cs.CLcs.LGarXiv:2608.30376v12026
Direct speech-to-speech translation with discrete units
Ann Lee, Peng-Jen Chen, Changhan Wang +9
cs.CLcs.LGeess.ASarXiv:2107.05604v22021
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes
Greg Yang
cs.NEcond-mat.dis-nncs.LGarXiv:1910.12478v32019
Federated Learning with Partial Model Personalization
Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed +3
cs.LGcs.DCmath.OCarXiv:2204.03809v22022
Learning Features of Music from Scratch
John Thickstun, Zaid Harchaoui, Sham Kakade
stat.MLcs.LGcs.SDarXiv:1611.09827v22016
A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning
Soochan Lee, Junsoo Ha, Dongsu Zhang +1
cs.LGcs.NEstat.MLarXiv:2001.00689v22020
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
Luhuan Wu, Brian L. Trippe, Christian A. Naesseth +2
stat.MLcs.LGq-bio.BMarXiv:2306.17775v22023
Beyond Token-Level Guidance: Inference-Time Alignment of Specialized LLMs via Cross-Family Representation Steering
Jin Gan, Xin Li, Jun Luo
cs.CLcs.AIcs.LGarXiv:2608.30319v12026
SparseFool: a few pixels make a big difference
Apostolos Modas, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard
cs.CVcs.CRcs.LGarXiv:1811.02248v42018
On Biased Compression for Distributed Learning
Aleksandr Beznosikov, Samuel Horváth, Peter Richtárik +1
cs.LGcs.DCmath.OCarXiv:2002.12410v42020
Using Prosody to Predict Syntactic Structure
Junghyun Min, Alex Warstadt, Tamar I. Regev +2
cs.CLcs.AIcs.LGarXiv:2608.30260v12026
Kolmogorov-Arnold Networks (KANs) for Time Series Analysis
Cristian J. Vaca-Rubio, Luis Blanco, Roberto Pereira +1
eess.SPcs.AIcs.LGarXiv:2405.08790v22024
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning
Matias Mendieta, Taojiannan Yang, Pu Wang +3
cs.LGcs.CVcs.DCarXiv:2111.14213v32021
Information-Based Calibration of Uncertainty Quantification in Product-of-Experts Gaussian Process Models
Yean Hoon Ong, Paolo Barucca, Wei Pan +1
cs.LGarXiv:2608.29349v12026
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

Machine Learning

Implicit Semantic Data Augmentation for Deep Networks

Federated Learning for Ultra-Reliable Low-Latency V2V Communications

Quantum circuit architecture search for variational quantum algorithms

DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality

Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges

Communication Algorithms via Deep Learning

Clustering as Approximation by Constrained Projectors: Theory and Guarantees

Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey

Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods

Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges

Ceiling-Clipped Acceptance Histograms Indicate Stranded Speed-up in Block-Diffusion Speculative Decoding

Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors

Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models

Leakage and the Reproducibility Crisis in ML-based Science

On the Origin of Deep Learning

StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text

RuleMatrix: Visualizing and Understanding Classifiers with Rules

Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression

Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control

ASlib: A Benchmark Library for Algorithm Selection

Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs

Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication

Feature Engineering for Predictive Modeling using Reinforcement Learning

Reward Model Ensembles Help Mitigate Overoptimization

3D-LaneNet: End-to-End 3D Multiple Lane Detection

Fully Distributed GNE Algorithms for Multi-Robot Placement without Consensus on Multipliers

Hyper-SAGNN: a self-attention based graph neural network for hypergraphs

Benchmarking Large Language Models for Automated Verilog RTL Code Generation

Kathleen Remembers: Length-Invariant One-Shot Recall Without Attention

Direct speech-to-speech translation with discrete units

Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes

Federated Learning with Partial Model Personalization

Learning Features of Music from Scratch

A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning

Practical and Asymptotically Exact Conditional Sampling in Diffusion Models

Beyond Token-Level Guidance: Inference-Time Alignment of Specialized LLMs via Cross-Family Representation Steering

SparseFool: a few pixels make a big difference

On Biased Compression for Distributed Learning

Using Prosody to Predict Syntactic Structure

Kolmogorov-Arnold Networks (KANs) for Time Series Analysis

Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning

Information-Based Calibration of Uncertainty Quantification in Product-of-Experts Gaussian Process Models

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