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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11,761 to 11,820 of 20,193

3D Infomax improves GNNs for Molecular Property Prediction
Hannes Stärk, Dominique Beaini, Gabriele Corso +4
cs.LGcs.AIq-bio.BMarXiv:2110.04126v42021
Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence
Tal Schuster, Adam Fisch, Regina Barzilay
cs.CLcs.IRcs.LGarXiv:2103.08541v12021
Function Vectors in Large Language Models
Eric Todd, Millicent L. Li, Arnab Sen Sharma +3
cs.CLcs.LGarXiv:2310.15213v22023
Towards Debiasing Sentence Representations
Paul Pu Liang, Irene Mengze Li, Emily Zheng +3
cs.CLcs.LGarXiv:2007.08100v12020
Unlocking High-Accuracy Differentially Private Image Classification through Scale
Soham De, Leonard Berrada, Jamie Hayes +2
cs.LGcs.CRcs.CVarXiv:2204.13650v22022
Delving into Out-of-Distribution Detection with Vision-Language Representations
Yifei Ming, Ziyang Cai, Jiuxiang Gu +3
cs.CVcs.AIcs.LGarXiv:2211.13445v12022
Bayesian Neural Networks: An Introduction and Survey
Ethan Goan, Clinton Fookes
stat.MLcs.LGarXiv:2006.12024v32020
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond
Anna Hedström, Leander Weber, Dilyara Bareeva +5
cs.LGarXiv:2202.06861v32022
Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery
Junjun Jiang, He Sun, Xianming Liu +1
eess.IVcs.CVcs.LGarXiv:2005.08752v22020
A statistical model for tensor PCA
Andrea Montanari, Emile Richard
cs.LGcs.ITstat.MLarXiv:1411.1076v12014
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
Lars Ruthotto, Stanley Osher, Wuchen Li +2
cs.LGmath.NAmath.OCarXiv:1912.01825v32019
Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies
Liangming Pan, Michael Saxon, Wenda Xu +3
cs.CLcs.AIcs.LGarXiv:2308.03188v22023
Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview
Deven Shah, H. Andrew Schwartz, Dirk Hovy
cs.CLcs.AIcs.LGarXiv:1912.11078v22019
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities
Enneng Yang, Li Shen, Guibing Guo +4
cs.LGcs.AIcs.CLarXiv:2408.07666v52024
Transfer Learning with Dynamic Distribution Adaptation
Jindong Wang, Yiqiang Chen, Wenjie Feng +3
cs.LGstat.MLarXiv:1909.08531v12019
Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups
Yani Ioannou, Duncan Robertson, Roberto Cipolla +1
cs.NEcs.CVcs.LGarXiv:1605.06489v32016
Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network
Martin Gauch, Frederik Kratzert, Daniel Klotz +3
cs.LGphysics.ao-pharXiv:2010.07921v12020
A Laplacian Framework for Option Discovery in Reinforcement Learning
Marlos C. Machado, Marc G. Bellemare, Michael Bowling
cs.LGcs.AIarXiv:1703.00956v22017
Learning to Act by Predicting the Future
Alexey Dosovitskiy, Vladlen Koltun
cs.LGcs.AIcs.CVarXiv:1611.01779v22016
Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity
Byungseok Roh, JaeWoong Shin, Wuhyun Shin +1
cs.CVcs.LGarXiv:2111.14330v22021
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
Yudong Chen, Lili Su, Jiaming Xu
cs.DCcs.CRcs.LGarXiv:1705.05491v22017
SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation
Xingyu Lin, Yufei Wang, Jake Olkin +1
cs.ROcs.LGarXiv:2011.07215v22020
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds
Xiaohan Chen, Jialin Liu, Zhangyang Wang +1
cs.LGstat.MLarXiv:1808.10038v22018
Continual Unsupervised Representation Learning
Dushyant Rao, Francesco Visin, Andrei A. Rusu +3
cs.LGcs.AIcs.CVarXiv:1910.14481v12019
Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions
Pouya Pezeshkpour, Estevam Hruschka
cs.CLcs.AIcs.LGarXiv:2308.11483v12023
A Survey of Domain Adaptation for Neural Machine Translation
Chenhui Chu, Rui Wang
cs.CLcs.AIcs.LGarXiv:1806.00258v12018
N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification
Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi +1
cs.LGcs.SIstat.MLarXiv:1802.08888v12018
CvxNet: Learnable Convex Decomposition
Boyang Deng, Kyle Genova, Soroosh Yazdani +3
cs.CVcs.GRcs.LGarXiv:1909.05736v42019
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning
Yu Yao, Tongliang Liu, Bo Han +4
cs.LGstat.MLarXiv:2006.07805v32020
Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures
Mengjia Yan, Christopher Fletcher, Josep Torrellas
cs.DCcs.CRcs.LGarXiv:1808.04761v12018
A Long Way to Go: Investigating Length Correlations in RLHF
Prasann Singhal, Tanya Goyal, Jiacheng Xu +1
cs.CLcs.LGarXiv:2310.03716v22023
I$^2$SB: Image-to-Image Schrödinger Bridge
Guan-Horng Liu, Arash Vahdat, De-An Huang +3
cs.CVcs.LGstat.MLarXiv:2302.05872v32023
RADAR: Robust AI-Text Detection via Adversarial Learning
Xiaomeng Hu, Pin-Yu Chen, Tsung-Yi Ho
cs.CLcs.AIcs.LGarXiv:2307.03838v22023
HAT: Hardware-Aware Transformers for Efficient Natural Language Processing
Hanrui Wang, Zhanghao Wu, Zhijian Liu +4
cs.CLcs.LGcs.NEarXiv:2005.14187v12020
Forward Compatible Few-Shot Class-Incremental Learning
Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye +3
cs.CVcs.LGarXiv:2203.06953v12022
Physics-informed neural network for ultrasound nondestructive quantification of surface breaking cracks
Khemraj Shukla, Patricio Clark Di Leoni, James Blackshire +2
cs.LGstat.MLarXiv:2005.03596v12020
Graph-based Semi-supervised Learning: A Comprehensive Review
Zixing Song, Xiangli Yang, Zenglin Xu +1
cs.LGarXiv:2102.13303v12021
A Crowdsourcing Framework for On-Device Federated Learning
Shashi Raj Pandey, Nguyen H. Tran, Mehdi Bennis +3
cs.LGcs.GTcs.NIarXiv:1911.01046v22019
Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks
Kunjin Chen, Jun Hu, Yu Zhang +2
cs.LGstat.APstat.MLarXiv:1812.09464v22018
Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions
Joey Hong, Benjamin Sapp, James Philbin
cs.CVcs.LGcs.ROarXiv:1906.08945v12019
Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use case
Paul Almasan, José Suárez-Varela, Krzysztof Rusek +2
cs.NIcs.LGarXiv:1910.07421v32019
Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence
Mert Pilanci, Martin J. Wainwright
math.OCcs.DScs.LGarXiv:1505.02250v12015
AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents
Harsh Trivedi, Tushar Khot, Mareike Hartmann +6
cs.SEcs.AIcs.CLarXiv:2407.18901v12024
Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
Yeongmin Ko, Younkwan Lee, Shoaib Azam +3
cs.CVcs.LGeess.IVarXiv:2002.06604v42020
Dopamine: A Research Framework for Deep Reinforcement Learning
Pablo Samuel Castro, Subhodeep Moitra, Carles Gelada +2
cs.LGcs.AIarXiv:1812.06110v12018
Towards Generalization and Simplicity in Continuous Control
Aravind Rajeswaran, Kendall Lowrey, Emanuel Todorov +1
cs.LGcs.AIcs.ROarXiv:1703.02660v22017
Human-robot collaboration and machine learning: a systematic review of recent research
Francesco Semeraro, Alexander Griffiths, Angelo Cangelosi
cs.ROcs.LGarXiv:2110.07448v42021
Bidirectional Recurrent Neural Networks for Medical Event Detection in Electronic Health Records
Abhyuday Jagannatha, Hong Yu
cs.CLcs.LGcs.NEarXiv:1606.07953v22016
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
Tianlong Chen, Sijia Liu, Shiyu Chang +3
cs.CVcs.LGarXiv:2003.12862v12020
Hybrid Reward Architecture for Reinforcement Learning
Harm van Seijen, Mehdi Fatemi, Joshua Romoff +3
cs.LGarXiv:1706.04208v22017
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks
Alexander Geiger, Dongyu Liu, Sarah Alnegheimish +2
cs.LGstat.MLarXiv:2009.07769v32020
Discovering Latent Network Structure in Point Process Data
Scott W. Linderman, Ryan P. Adams
stat.MLcs.LGarXiv:1402.0914v12014
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy
Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann +4
stat.MLcs.AIcs.LGarXiv:1611.04488v62016
Differentially Private Model Publishing for Deep Learning
Lei Yu, Ling Liu, Calton Pu +2
cs.CRcs.LGarXiv:1904.02200v52019
RODE: Learning Roles to Decompose Multi-Agent Tasks
Tonghan Wang, Tarun Gupta, Anuj Mahajan +3
cs.LGstat.MLarXiv:2010.01523v12020
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization
Constantinos Daskalakis, Ioannis Panageas
math.OCcs.LGstat.MLarXiv:1807.03907v22018
Efficient Learning of Domain-invariant Image Representations
Judy Hoffman, Erik Rodner, Jeff Donahue +2
cs.LGarXiv:1301.3224v52013
SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations
Qitian Wu, Wentao Zhao, Chenxiao Yang +5
cs.LGcs.AIcs.SIarXiv:2306.10759v52023
A Large Self-Annotated Corpus for Sarcasm
Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli
cs.CLcs.AIcs.LGarXiv:1704.05579v42017
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Biao Zhang, Zhongtao Liu, Colin Cherry +1
cs.CLcs.LGarXiv:2402.17193v12024

Machine Learning

3D Infomax improves GNNs for Molecular Property Prediction

Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence

Function Vectors in Large Language Models

Towards Debiasing Sentence Representations

Unlocking High-Accuracy Differentially Private Image Classification through Scale

Delving into Out-of-Distribution Detection with Vision-Language Representations

Bayesian Neural Networks: An Introduction and Survey

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond

Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery

A statistical model for tensor PCA

A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems

Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies

Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities

Transfer Learning with Dynamic Distribution Adaptation

Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups

Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network

A Laplacian Framework for Option Discovery in Reinforcement Learning

Learning to Act by Predicting the Future

Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent

SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation

Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds

Continual Unsupervised Representation Learning

Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions

A Survey of Domain Adaptation for Neural Machine Translation

N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification

CvxNet: Learnable Convex Decomposition

Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning

Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures

A Long Way to Go: Investigating Length Correlations in RLHF

I$^2$SB: Image-to-Image Schrödinger Bridge

RADAR: Robust AI-Text Detection via Adversarial Learning

HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

Forward Compatible Few-Shot Class-Incremental Learning

Physics-informed neural network for ultrasound nondestructive quantification of surface breaking cracks

Graph-based Semi-supervised Learning: A Comprehensive Review

A Crowdsourcing Framework for On-Device Federated Learning

Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks

Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions

Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use case

Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence

AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents

Key Points Estimation and Point Instance Segmentation Approach for Lane Detection

Dopamine: A Research Framework for Deep Reinforcement Learning

Towards Generalization and Simplicity in Continuous Control

Human-robot collaboration and machine learning: a systematic review of recent research

Bidirectional Recurrent Neural Networks for Medical Event Detection in Electronic Health Records

Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning

Hybrid Reward Architecture for Reinforcement Learning

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks

Discovering Latent Network Structure in Point Process Data

Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy

Differentially Private Model Publishing for Deep Learning

RODE: Learning Roles to Decompose Multi-Agent Tasks

The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization

Efficient Learning of Domain-invariant Image Representations

SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations

A Large Self-Annotated Corpus for Sarcasm

When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method