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.

Search paper metadata (including unsummarized papers)

18,481 to 18,540 of 20,199

ImageBind: One Embedding Space To Bind Them All
Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu +4
cs.CVcs.AIcs.LGarXiv:2305.05665v22023
A guide to convolution arithmetic for deep learning
Vincent Dumoulin, Francesco Visin
stat.MLcs.LGcs.NEarXiv:1603.07285v22016
Multiscale Vision Transformers
Haoqi Fan, Bo Xiong, Karttikeya Mangalam +4
cs.CVcs.AIcs.LGarXiv:2104.11227v12021
Learning to Reweight Examples for Robust Deep Learning
Mengye Ren, Wenyuan Zeng, Bin Yang +1
cs.LGstat.MLarXiv:1803.09050v32018
Generative Adversarial Network in Medical Imaging: A Review
Xin Yi, Ekta Walia, Paul Babyn
cs.CVcs.LGarXiv:1809.07294v42018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
Yujun Lin, Song Han, Huizi Mao +2
cs.CVcs.DCcs.LGarXiv:1712.01887v32017
MINE: Mutual Information Neural Estimation
Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar +4
cs.LGstat.MLarXiv:1801.04062v52018
Differentially Private Federated Learning: A Client Level Perspective
Robin C. Geyer, Tassilo Klein, Moin Nabi
cs.CRcs.LGstat.MLarXiv:1712.07557v22017
Deep learning for universal linear embeddings of nonlinear dynamics
Bethany Lusch, J. Nathan Kutz, Steven L. Brunton
math.DScs.LGstat.MLarXiv:1712.09707v22017
Mitigating Unwanted Biases with Adversarial Learning
Brian Hu Zhang, Blake Lemoine, Margaret Mitchell
cs.LGcs.AIcs.CYarXiv:1801.07593v12018
LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
Abhishek Chaurasia, Eugenio Culurciello
cs.CVcs.LGarXiv:1707.03718v12017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
Weilin Xu, David Evans, Yanjun Qi
cs.CVcs.CRcs.LGarXiv:1704.01155v22017
A Review of Relational Machine Learning for Knowledge Graphs
Maximilian Nickel, Kevin Murphy, Volker Tresp +1
stat.MLcs.LGarXiv:1503.00759v32015
Poincaré Embeddings for Learning Hierarchical Representations
Maximilian Nickel, Douwe Kiela
cs.AIcs.LGstat.MLarXiv:1705.08039v22017
Joint Training of Multi-Token Prediction in Reinforcement Learning via Optimal Coefficient Calibration
Zili Wang, Jiajun Chai, Lin Chen +3
cs.LGarXiv:2605.28184v12026
Heterogeneous Graph Transformer
Ziniu Hu, Yuxiao Dong, Kuansan Wang +1
cs.LGcs.SIstat.MLarXiv:2003.01332v12020
Ray: A Distributed Framework for Emerging AI Applications
Philipp Moritz, Robert Nishihara, Stephanie Wang +8
cs.DCcs.AIcs.LGarXiv:1712.05889v22017
How Does Batch Normalization Help Optimization?
Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas +1
stat.MLcs.LGcs.NEarXiv:1805.11604v52018
Adversarial Examples for Evaluating Reading Comprehension Systems
Robin Jia, Percy Liang
cs.CLcs.LGarXiv:1707.07328v12017
Inverting Gradients -- How easy is it to break privacy in federated learning?
Jonas Geiping, Hartmut Bauermeister, Hannah Dröge +1
cs.CVcs.CRcs.LGarXiv:2003.14053v22020
QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor +8
cs.LGcs.AIcs.CVarXiv:1806.10293v32018
Exploration by Random Network Distillation
Yuri Burda, Harrison Edwards, Amos Storkey +1
cs.LGcs.AIstat.MLarXiv:1810.12894v12018
Alignment Tampering: How Reinforcement Learning from Human Feedback Is Exploited to Optimize Misaligned Biases
Dongyoon Hahm, Dylan Hadfield-Menell, Kimin Lee
cs.AIcs.CLcs.LGarXiv:2605.27355v22026
Grounded Language-Image Pre-training
Liunian Harold Li, Pengchuan Zhang, Haotian Zhang +9
cs.CVcs.AIcs.CLarXiv:2112.03857v22021
Interpretable Explanations of Black Boxes by Meaningful Perturbation
Ruth Fong, Andrea Vedaldi
cs.CVcs.AIcs.LGarXiv:1704.03296v42017
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting
Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados +1
cs.LGstat.MLarXiv:1905.10437v42019
Contrastive Multi-View Representation Learning on Graphs
Kaveh Hassani, Amir Hosein Khasahmadi
cs.LGstat.MLarXiv:2006.05582v12020
DEI: Diversity in Evolutionary Inference for Quality-Diversity Search
John Donaghy, Shikhar Rastogi
cs.LGcs.AIarXiv:2605.27130v12026
DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation
Yizhe Zhang, Siqi Sun, Michel Galley +6
cs.CLcs.LGarXiv:1911.00536v32019
How multilingual is Multilingual BERT?
Telmo Pires, Eva Schlinger, Dan Garrette
cs.CLcs.AIcs.LGarXiv:1906.01502v12019
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Jie Chen, Tengfei Ma, Cao Xiao
cs.LGarXiv:1801.10247v12018
PEFT-Arena: Understanding Parameter-Efficient Finetuning from a Stability-Plasticity Perspective
Yangyi Huang, Ruotian Peng, Zeju Qiu +4
cs.LGcs.CLarXiv:2605.28819v12026
Why GPT-Style Models Do Not Directly Transfer to Symbolic Music: Compression in the Wrong Coordinate System
Yi Wang
cs.LGcs.AIcs.SDarXiv:2608.18025v12026
AsyncOPD: How Stale Can On-Policy Distillation Be?
Wonjun Kang, Kevin Galim, Seunghyuk Oh +9
cs.LGarXiv:2606.24143v12026
How To Backdoor Federated Learning
Eugene Bagdasaryan, Andreas Veit, Yiqing Hua +2
cs.CRcs.LGarXiv:1807.00459v32018
PhyCo: Learning Controllable Physical Priors for Generative Motion
Sriram Narayanan, Ziyu Jiang, Srinivasa Narasimhan +1
cs.CVcs.AIcs.LGarXiv:2604.28169v12026
Summaries:한국어
TabNet: Attentive Interpretable Tabular Learning
Sercan O. Arik, Tomas Pfister
cs.LGstat.MLarXiv:1908.07442v52019
ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation
Hongru Hou, Tiehua Mei, Denghui Geng +5
cs.LGcs.AIarXiv:2605.28293v22026
CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society
Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani +2
cs.AIcs.CLcs.CYarXiv:2303.17760v22023
Learn from Weaknesses: Automated Domain Specialization for Small Computer-Use Agents
Suji Kim, Kangsan Kim, Sung Ju Hwang
cs.LGcs.AIcs.CLarXiv:2605.28775v12026
A Survey of Deep Learning Techniques for Autonomous Driving
Sorin Grigorescu, Bogdan Trasnea, Tiberiu Cocias +1
cs.LGcs.ROarXiv:1910.07738v22019
Generation and Comprehension of Unambiguous Object Descriptions
Junhua Mao, Jonathan Huang, Alexander Toshev +3
cs.CVcs.CLcs.LGarXiv:1511.02283v32015
Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal
Junlin Wang
cs.ROcs.LGarXiv:2605.27919v12026
Experience Replay for Continual Learning
David Rolnick, Arun Ahuja, Jonathan Schwarz +2
cs.LGcs.AIstat.MLarXiv:1811.11682v22018
Deep Metric Learning via Lifted Structured Feature Embedding
Hyun Oh Song, Yu Xiang, Stefanie Jegelka +1
cs.CVcs.LGarXiv:1511.06452v12015
Fully Convolutional Siamese Networks for Change Detection
Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch
cs.CVcs.LGarXiv:1810.08462v12018
Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization
Hao Jiang, Shurui Li, Tianpeng Bu +7
cs.LGarXiv:2605.28109v12026
Rethinking Memory as Continuously Evolving Connectivity
Jizhan Fang, Buqiang Xu, Zhixian Wang +12
cs.CLcs.AIcs.LGarXiv:2605.28773v12026
The Hamilton-Jacobi Theory of Deep Learning
Jose Marie Antonio Miñoza, Erika Fille T. Legara, Christopher P. Monterola
cs.LGcs.AImath.DSarXiv:2605.28983v22026
Training Very Deep Networks
Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber
cs.LGcs.NEarXiv:1507.06228v22015
Deep Anomaly Detection with Outlier Exposure
Dan Hendrycks, Mantas Mazeika, Thomas Dietterich
cs.LGcs.CLcs.CVarXiv:1812.04606v32018
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Niranjan Srinivas, Andreas Krause, Sham M. Kakade +1
cs.LGarXiv:0912.3995v42009
Sequence Level Training with Recurrent Neural Networks
Marc'Aurelio Ranzato, Sumit Chopra, Michael Auli +1
cs.LGcs.CLarXiv:1511.06732v72015
Augmenting Attention with Exponentially Decaying Memory Improves Query-Aware KV Sparsity
Xiuying Wei, Caglar Gulcehre
cs.LGarXiv:2605.28640v12026
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
Takayuki Nishio, Ryo Yonetani
cs.NIcs.LGarXiv:1804.08333v22018
Self-supervised Graph Learning for Recommendation
Jiancan Wu, Xiang Wang, Fuli Feng +4
cs.IRcs.LGarXiv:2010.10783v42020
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
Iulian V. Serban, Alessandro Sordoni, Yoshua Bengio +2
cs.CLcs.AIcs.LGarXiv:1507.04808v32015
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Tri Dao, Albert Gu
cs.LGarXiv:2405.21060v12024
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
Guangxuan Xiao, Ji Lin, Mickael Seznec +3
cs.CLcs.AIcs.LGarXiv:2211.10438v72022
LaRA: Layer-wise Representation Analysis for Detecting Data Contamination in RL Post-Training
Minju Gwak, Minseo Kwak, Dongseok Lee +3
cs.LGcs.AIarXiv:2605.29888v12026

Machine Learning

ImageBind: One Embedding Space To Bind Them All

A guide to convolution arithmetic for deep learning

Multiscale Vision Transformers

Learning to Reweight Examples for Robust Deep Learning

Generative Adversarial Network in Medical Imaging: A Review

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

MINE: Mutual Information Neural Estimation

Differentially Private Federated Learning: A Client Level Perspective

Deep learning for universal linear embeddings of nonlinear dynamics

Mitigating Unwanted Biases with Adversarial Learning

LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation

Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks

A Review of Relational Machine Learning for Knowledge Graphs

Poincaré Embeddings for Learning Hierarchical Representations

Joint Training of Multi-Token Prediction in Reinforcement Learning via Optimal Coefficient Calibration

Heterogeneous Graph Transformer

Ray: A Distributed Framework for Emerging AI Applications

How Does Batch Normalization Help Optimization?

Adversarial Examples for Evaluating Reading Comprehension Systems

Inverting Gradients -- How easy is it to break privacy in federated learning?

QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation

Exploration by Random Network Distillation

Alignment Tampering: How Reinforcement Learning from Human Feedback Is Exploited to Optimize Misaligned Biases

Grounded Language-Image Pre-training

Interpretable Explanations of Black Boxes by Meaningful Perturbation

N-BEATS: Neural basis expansion analysis for interpretable time series forecasting

Contrastive Multi-View Representation Learning on Graphs

DEI: Diversity in Evolutionary Inference for Quality-Diversity Search

DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation

How multilingual is Multilingual BERT?

FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

PEFT-Arena: Understanding Parameter-Efficient Finetuning from a Stability-Plasticity Perspective

Why GPT-Style Models Do Not Directly Transfer to Symbolic Music: Compression in the Wrong Coordinate System

AsyncOPD: How Stale Can On-Policy Distillation Be?

How To Backdoor Federated Learning

PhyCo: Learning Controllable Physical Priors for Generative Motion

TabNet: Attentive Interpretable Tabular Learning

ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation

CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society

Learn from Weaknesses: Automated Domain Specialization for Small Computer-Use Agents

A Survey of Deep Learning Techniques for Autonomous Driving

Generation and Comprehension of Unambiguous Object Descriptions

Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal

Experience Replay for Continual Learning

Deep Metric Learning via Lifted Structured Feature Embedding

Fully Convolutional Siamese Networks for Change Detection

Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization

Rethinking Memory as Continuously Evolving Connectivity

The Hamilton-Jacobi Theory of Deep Learning

Training Very Deep Networks

Deep Anomaly Detection with Outlier Exposure

Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Sequence Level Training with Recurrent Neural Networks

Augmenting Attention with Exponentially Decaying Memory Improves Query-Aware KV Sparsity

Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge

Self-supervised Graph Learning for Recommendation

Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models

Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

LaRA: Layer-wise Representation Analysis for Detecting Data Contamination in RL Post-Training