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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21,601 to 21,660 of 33,200

Driver Distraction Identification with an Ensemble of Convolutional Neural Networks
Hesham M. Eraqi, Yehya Abouelnaga, Mohamed H. Saad +1
cs.CVcs.LGstat.MLarXiv:1901.09097v12019
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing
Yu Gu, Robert Tinn, Hao Cheng +6
cs.CLcs.LGarXiv:2007.15779v62020
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
Christian Schlarmann, Naman Deep Singh, Francesco Croce +1
cs.LGcs.AIcs.CVarXiv:2402.12336v22024
Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation
Po-Sen Huang, Minje Kim, Mark Hasegawa-Johnson +1
cs.SDcs.AIcs.LGarXiv:1502.04149v42015
Federated Learning with Differential Privacy: Algorithms and Performance Analysis
Kang Wei, Jun Li, Ming Ding +6
cs.LGcs.NIarXiv:1911.00222v22019
SecureBoost: A Lossless Federated Learning Framework
Kewei Cheng, Tao Fan, Yilun Jin +4
cs.LGstat.MLarXiv:1901.08755v32019
ProCTI: Prototype-Refined Global Conditioning for Diffusion-Based Time Series Imputation
Fariza Rashid, Duc Van Le, Rahat Masood +3
cs.LGcs.AIarXiv:2609.37632v12026
Robust and interpretable blind image denoising via bias-free convolutional neural networks
Sreyas Mohan, Zahra Kadkhodaie, Eero P. Simoncelli +1
eess.IVcs.CVcs.LGarXiv:1906.05478v32019
Foolbox: A Python toolbox to benchmark the robustness of machine learning models
Jonas Rauber, Wieland Brendel, Matthias Bethge
cs.LGcs.CRcs.CVarXiv:1707.04131v32017
Towards Explainable Deep Neural Networks (xDNN)
Plamen Angelov, Eduardo Soares
cs.LGcs.AIcs.CVarXiv:1912.02523v12019
Sparse Stochastic Inference for Latent Dirichlet allocation
David Mimno, Matt Hoffman, David Blei
cs.LGstat.MLarXiv:1206.6425v12012
Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks
Young-Jun Lee, Seungone Kim, Minki Kang +5
cs.CLcs.LGarXiv:2606.29082v12026
A Survey of Malware Detection Using Deep Learning
Ahmed Bensaoud, Jugal Kalita, Mahmoud Bensaoud
cs.CRcs.LGarXiv:2407.19153v12024
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing, Yichen Shen, Tena Dubček +5
cs.LGcs.NEstat.MLarXiv:1612.05231v32016
EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments
Deyao Zhu, Xin Zhou, Shengling Qin +44
cs.CLcs.LGarXiv:2607.05155v12026
Enhancing Object Detection with Privileged Information: A Model-Agnostic Teacher-Student Approach
Matthias Bartolo, Dylan Seychell, Gabriel Hili +4
cs.CVcs.AIcs.ETarXiv:2601.02016v12026
Hypergraph Convolution and Hypergraph Attention
Song Bai, Feihu Zhang, Philip H. S. Torr
cs.LGcs.CVstat.MLarXiv:1901.08150v22019
Human Pose Regression with Residual Log-likelihood Estimation
Jiefeng Li, Siyuan Bian, Ailing Zeng +4
cs.CVcs.LGarXiv:2107.11291v32021
Deep K-SVD Denoising
Meyer Scetbon, Michael Elad, Peyman Milanfar
cs.LGstat.MLarXiv:1909.13164v22019
SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting
Binbin Zheng, Xing Ma, Yiheng Liang +6
cs.LGcs.AIcs.CLarXiv:2604.10688v22026
Lower Bounds for Non-Convex Stochastic Optimization
Yossi Arjevani, Yair Carmon, John C. Duchi +3
math.OCcs.ITcs.LGarXiv:1912.02365v22019
Differentially Private Release and Learning of Threshold Functions
Mark Bun, Kobbi Nissim, Uri Stemmer +1
cs.CRcs.LGarXiv:1504.07553v22015
Reevaluating Adversarial Examples in Natural Language
John X. Morris, Eli Lifland, Jack Lanchantin +2
cs.CLcs.AIcs.CRarXiv:2004.14174v32020
El Agente: An Autonomous Agent for Quantum Chemistry
Yunheng Zou, Austin H. Cheng, Abdulrahman Aldossary +13
cs.AIcs.LGcs.MAarXiv:2505.02484v22025
A predictive safety filter for learning-based control of constrained nonlinear dynamical systems
Kim P. Wabersich, Melanie N. Zeilinger
eess.SYcs.LGarXiv:1812.05506v42018
Breaking the Curse of Dimensionality with Convex Neural Networks
Francis Bach
cs.LGmath.OCmath.STarXiv:1412.8690v22014
Temporal Attentive Alignment for Large-Scale Video Domain Adaptation
Min-Hung Chen, Zsolt Kira, Ghassan AlRegib +3
cs.CVcs.LGcs.MMarXiv:1907.12743v62019
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer
Hongyan Chang, Virat Shejwalkar, Reza Shokri +1
stat.MLcs.CRcs.LGarXiv:1912.11279v12019
On the Representational Geometry of Dynamic Programs
Richard F. M. Lim, Ruriko Yoshida
cs.LGcs.DMmath.AGarXiv:2608.25034v12026
Quadratic Autoencoder (Q-AE) for Low-dose CT Denoising
Fenglei Fan, Hongming Shan, Mannudeep K. Kalra +6
cs.LGeess.SPstat.MLarXiv:1901.05593v52019
Nonsense Helps: Prompt Space Perturbation Broadens Reasoning Exploration
Langlin Huang, Chengsong Huang, Jinyuan Li +3
cs.AIcs.CLcs.LGarXiv:2605.05566v12026
TasselNet: Counting maize tassels in the wild via local counts regression network
Hao Lu, Zhiguo Cao, Yang Xiao +2
cs.CVcs.LGarXiv:1707.02290v12017
The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations
A. Chatzimparmpas, R. Martins, I. Jusufi +3
cs.LGcs.HCstat.MLarXiv:2212.11737v22022
Cascading Gradient Inversion via LT-Code Inspired Peeling in Federated Learning
Saeed Shariati, Mohsen Alambardar Meybodi
cs.LGcs.AIcs.CRarXiv:2609.09659v12026
Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models
Yu Zeng, Wenxuan Huang, Zhen Fang +14
cs.CVcs.AIcs.CLarXiv:2602.02185v22026
Attributed Network Embedding for Learning in a Dynamic Environment
Jundong Li, Harsh Dani, Xia Hu +3
cs.SIcs.LGstat.MLarXiv:1706.01860v22017
How to use and interpret activation patching
Stefan Heimersheim, Neel Nanda
cs.LGarXiv:2404.15255v12024
SparLeak: Privacy Leakage from Sparse Attention in LLM Inference on Shared GPUs
Fahao Chen, Linkang Du, Jinhao Zhou +2
cs.LGcs.CRarXiv:2609.38830v12026
A statistical interpretation of spectral embedding: the generalised random dot product graph
Patrick Rubin-Delanchy, Joshua Cape, Minh Tang +1
stat.MLcs.LGarXiv:1709.05506v52017
Generalized Radiograph Representation Learning via Cross-supervision between Images and Free-text Radiology Reports
Hong-Yu Zhou, Xiaoyu Chen, Yinghao Zhang +3
eess.IVcs.CVcs.LGarXiv:2111.03452v22021
Reinforcement Learning via Self-Distillation
Jonas Hübotter, Frederike Lübeck, Lejs Behric +8
cs.LGcs.AIarXiv:2601.20802v22026
Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
Yiyang Zhou, Chenhang Cui, Rafael Rafailov +2
cs.LGcs.CLcs.CVarXiv:2402.11411v12024
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks
Yushun Dong, Ninghao Liu, Brian Jalaian +1
cs.LGarXiv:2108.05233v22021
Trajectory Design for UAV-Based Internet-of-Things Data Collection: A Deep Reinforcement Learning Approach
Yang Wang, Zhen Gao, Jun Zhang +5
cs.ITcs.LGeess.SParXiv:2107.11015v12021
Learning from Suboptimal Demonstration via Self-Supervised Reward Regression
Letian Chen, Rohan Paleja, Matthew Gombolay
cs.ROcs.LGarXiv:2010.11723v32020
Fantastic Generalization Measures and Where to Find Them
Yiding Jiang, Behnam Neyshabur, Hossein Mobahi +2
cs.LGstat.MLarXiv:1912.02178v12019
Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning
Xiaopeng Yan, Ziliang Chen, Anni Xu +3
cs.CVcs.LGarXiv:1909.13032v22019
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Esteban Real, Chen Liang, David R. So +1
cs.LGcs.NEstat.MLarXiv:2003.03384v22020
Fair Algorithms for Clustering
Suman K. Bera, Deeparnab Chakrabarty, Nicolas J. Flores +1
cs.DScs.LGarXiv:1901.02393v22019
Valdi: Value Diffusion World Models
Christopher Lindenberg, Kashyap Chitta
cs.LGcs.AIarXiv:2607.00917v12026
ACE-RTL: When Agentic Context Evolution Meets RTL-Specialized LLMs
Chenhui Deng, Zhongzhi Yu, Guan-Ting Liu +3
cs.ARcs.LGarXiv:2602.10218v22026
Review of Deep Learning
Rong Zhang, Weiping Li, Tong Mo
cs.LGcs.CVcs.NEarXiv:1804.01653v22018
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity
Peng Liao, Kristjan Greenewald, Predrag Klasnja +1
cs.LGcs.AIarXiv:1909.03539v12019
PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference
Xutao Wang, Hanting Chen, Tianyu Guo +1
cs.LGarXiv:2607.13428v12026
Kymatio: Scattering Transforms in Python
Mathieu Andreux, Tomás Angles, Georgios Exarchakis +15
cs.LGcs.CVcs.SDarXiv:1812.11214v32018
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)
Alex Fang, Gabriel Ilharco, Mitchell Wortsman +4
cs.CVcs.CLcs.LGarXiv:2205.01397v22022
Reconstructing subclonal composition and evolution from whole genome sequencing of tumors
Amit G. Deshwar, Shankar Vembu, Christina K. Yung +3
q-bio.PEcs.LGstat.MLarXiv:1406.7250v32014
EnergyStar++: Towards more accurate and explanatory building energy benchmarking
Pandarasamy Arjunan, Kameshwar Poolla, Clayton Miller
stat.APcs.LGeess.SYarXiv:1910.14563v22019
Deep linear neural networks with arbitrary loss: All local minima are global
Thomas Laurent, James von Brecht
cs.LGstat.MLarXiv:1712.01473v22017
Multi-Armed Bandits in Metric Spaces
Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal
cs.DScs.LGarXiv:0809.4882v12008

Machine Learning

Driver Distraction Identification with an Ensemble of Convolutional Neural Networks

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models

Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation

Federated Learning with Differential Privacy: Algorithms and Performance Analysis

SecureBoost: A Lossless Federated Learning Framework

ProCTI: Prototype-Refined Global Conditioning for Diffusion-Based Time Series Imputation

Robust and interpretable blind image denoising via bias-free convolutional neural networks

Foolbox: A Python toolbox to benchmark the robustness of machine learning models

Towards Explainable Deep Neural Networks (xDNN)

Sparse Stochastic Inference for Latent Dirichlet allocation

Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks

A Survey of Malware Detection Using Deep Learning

Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs

EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments

Enhancing Object Detection with Privileged Information: A Model-Agnostic Teacher-Student Approach

Hypergraph Convolution and Hypergraph Attention

Human Pose Regression with Residual Log-likelihood Estimation

Deep K-SVD Denoising

SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting

Lower Bounds for Non-Convex Stochastic Optimization

Differentially Private Release and Learning of Threshold Functions

Reevaluating Adversarial Examples in Natural Language

El Agente: An Autonomous Agent for Quantum Chemistry

A predictive safety filter for learning-based control of constrained nonlinear dynamical systems

Breaking the Curse of Dimensionality with Convex Neural Networks

Temporal Attentive Alignment for Large-Scale Video Domain Adaptation

Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer

On the Representational Geometry of Dynamic Programs

Quadratic Autoencoder (Q-AE) for Low-dose CT Denoising

Nonsense Helps: Prompt Space Perturbation Broadens Reasoning Exploration

TasselNet: Counting maize tassels in the wild via local counts regression network

The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations

Cascading Gradient Inversion via LT-Code Inspired Peeling in Federated Learning

Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models

Attributed Network Embedding for Learning in a Dynamic Environment

How to use and interpret activation patching

SparLeak: Privacy Leakage from Sparse Attention in LLM Inference on Shared GPUs

A statistical interpretation of spectral embedding: the generalised random dot product graph

Generalized Radiograph Representation Learning via Cross-supervision between Images and Free-text Radiology Reports

Reinforcement Learning via Self-Distillation

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks

Trajectory Design for UAV-Based Internet-of-Things Data Collection: A Deep Reinforcement Learning Approach

Learning from Suboptimal Demonstration via Self-Supervised Reward Regression

Fantastic Generalization Measures and Where to Find Them

Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning

AutoML-Zero: Evolving Machine Learning Algorithms From Scratch

Fair Algorithms for Clustering

Valdi: Value Diffusion World Models

ACE-RTL: When Agentic Context Evolution Meets RTL-Specialized LLMs

Review of Deep Learning

Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity

PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference

Kymatio: Scattering Transforms in Python

Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)

Reconstructing subclonal composition and evolution from whole genome sequencing of tumors

EnergyStar++: Towards more accurate and explanatory building energy benchmarking

Deep linear neural networks with arbitrary loss: All local minima are global

Multi-Armed Bandits in Metric Spaces