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)

12,901 to 12,960 of 20,193

Deep learning: a statistical viewpoint
Peter L. Bartlett, Andrea Montanari, Alexander Rakhlin
math.STcs.LGstat.MLarXiv:2103.09177v12021
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes
Xiaoyu Li, Francesco Orabona
stat.MLcs.LGmath.OCarXiv:1805.08114v32018
WikiHow: A Large Scale Text Summarization Dataset
Mahnaz Koupaee, William Yang Wang
cs.CLcs.IRcs.LGarXiv:1810.09305v12018
What graph neural networks cannot learn: depth vs width
Andreas Loukas
cs.LGstat.MLarXiv:1907.03199v22019
AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Images
Gongping Chen, Yu Dai, Jianxun Zhang +1
eess.IVcs.CVcs.LGarXiv:2204.12077v32022
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning
Sijia Liu, Pin-Yu Chen, Bhavya Kailkhura +3
cs.LGeess.SPstat.MLarXiv:2006.06224v22020
An exact mapping between the Variational Renormalization Group and Deep Learning
Pankaj Mehta, David J. Schwab
stat.MLcond-mat.stat-mechcs.LGarXiv:1410.3831v12014
ASD-DiagNet: A hybrid learning approach for detection of Autism Spectrum Disorder using fMRI data
Taban Eslami, Vahid Mirjalili, Alvis Fong +2
cs.LGeess.IVstat.MLarXiv:1904.07577v12019
Dual Discriminator Generative Adversarial Nets
Tu Dinh Nguyen, Trung Le, Hung Vu +1
cs.LGstat.MLarXiv:1709.03831v12017
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang +4
cs.LGcs.SIarXiv:2103.03212v22021
Label-Free Concept Bottleneck Models
Tuomas Oikarinen, Subhro Das, Lam M. Nguyen +1
cs.LGcs.CVarXiv:2304.06129v22023
Discovering Discrete Latent Topics with Neural Variational Inference
Yishu Miao, Edward Grefenstette, Phil Blunsom
cs.CLcs.AIcs.IRarXiv:1706.00359v22017
Physics informed deep learning for computational elastodynamics without labeled data
Chengping Rao, Hao Sun, Yang Liu
math.NAcs.AIcs.CEarXiv:2006.08472v12020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
Ines Chami, Sami Abu-El-Haija, Bryan Perozzi +2
cs.LGcs.NEcs.SIarXiv:2005.03675v32020
An introduction to domain adaptation and transfer learning
Wouter M. Kouw, Marco Loog
cs.LGcs.CVstat.MLarXiv:1812.11806v22018
Detecting and Preventing Hallucinations in Large Vision Language Models
Anisha Gunjal, Jihan Yin, Erhan Bas
cs.CVcs.LGarXiv:2308.06394v32023
Aerial Imagery Pile burn detection using Deep Learning: the FLAME dataset
Alireza Shamsoshoara, Fatemeh Afghah, Abolfazl Razi +3
cs.CVcs.AIcs.LGarXiv:2012.14036v12020
Robustness via curvature regularization, and vice versa
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Jonathan Uesato +1
cs.LGcs.CVstat.MLarXiv:1811.09716v12018
Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection
Yu Bai, Fan Chen, Huan Wang +2
cs.LGcs.AIcs.CLarXiv:2306.04637v22023
MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training
Yizhi Li, Ruibin Yuan, Ge Zhang +17
cs.SDcs.AIcs.CLarXiv:2306.00107v52023
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging
Mathias Perslev, Michael Hejselbak Jensen, Sune Darkner +2
cs.LGeess.SPstat.MLarXiv:1910.11162v12019
Evaluating Large Language Models at Evaluating Instruction Following
Zhiyuan Zeng, Jiatong Yu, Tianyu Gao +3
cs.CLcs.LGarXiv:2310.07641v22023
Transolver: A Fast Transformer Solver for PDEs on General Geometries
Haixu Wu, Huakun Luo, Haowen Wang +2
cs.LGmath.NAarXiv:2402.02366v22024
Deep Learning for Environmentally Robust Speech Recognition: An Overview of Recent Developments
Zixing Zhang, Jürgen Geiger, Jouni Pohjalainen +3
cs.SDcs.CLcs.LGarXiv:1705.10874v32017
Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI
Yang Liu, Weixing Chen, Yongjie Bai +4
cs.CVcs.AIcs.LGarXiv:2407.06886v82024
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
Yoshitomo Matsubara, Marco Levorato, Francesco Restuccia
eess.SPcs.LGarXiv:2103.04505v42021
Understanding the Acceleration Phenomenon via High-Resolution Differential Equations
Bin Shi, Simon S. Du, Michael I. Jordan +1
math.OCcs.LGmath.CAarXiv:1810.08907v32018
Generative Probabilistic Novelty Detection with Adversarial Autoencoders
Stanislav Pidhorskyi, Ranya Almohsen, Donald A Adjeroh +1
cs.CVcs.LGarXiv:1807.02588v22018
Neural Networks with Few Multiplications
Zhouhan Lin, Matthieu Courbariaux, Roland Memisevic +1
cs.LGcs.NEarXiv:1510.03009v32015
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models
Avi Singh, John D. Co-Reyes, Rishabh Agarwal +38
cs.LGarXiv:2312.06585v42023
Learning Robust Representations via Multi-View Information Bottleneck
Marco Federici, Anjan Dutta, Patrick Forré +2
cs.LGstat.MLarXiv:2002.07017v22020
Underdamped Langevin MCMC: A non-asymptotic analysis
Xiang Cheng, Niladri S. Chatterji, Peter L. Bartlett +1
stat.MLcs.LGstat.COarXiv:1707.03663v72017
Learning without Concentration
Shahar Mendelson
cs.LGstat.MLarXiv:1401.0304v22014
Learning Sparse Nonparametric DAGs
Xun Zheng, Chen Dan, Bryon Aragam +2
stat.MLcs.LGstat.MEarXiv:1909.13189v22019
First-order Methods for Geodesically Convex Optimization
Hongyi Zhang, Suvrit Sra
math.OCcs.LGstat.MLarXiv:1602.06053v12016
Proximal Newton-type methods for minimizing composite functions
Jason D. Lee, Yuekai Sun, Michael A. Saunders
stat.MLcs.DScs.LGarXiv:1206.1623v132012
Explanations in Autonomous Driving: A Survey
Daniel Omeiza, Helena Webb, Marina Jirotka +1
cs.HCcs.AIcs.CYarXiv:2103.05154v42021
Reinforcement and Imitation Learning for Diverse Visuomotor Skills
Yuke Zhu, Ziyu Wang, Josh Merel +8
cs.ROcs.AIcs.LGarXiv:1802.09564v22018
Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice
Jeroen Bertels, Tom Eelbode, Maxim Berman +4
cs.CVcs.LGeess.IVarXiv:1911.01685v12019
Analyzing the Behavior of Visual Question Answering Models
Aishwarya Agrawal, Dhruv Batra, Devi Parikh
cs.CLcs.AIcs.CVarXiv:1606.07356v22016
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs
Albert Q. Jiang, Sean Welleck, Jin Peng Zhou +6
cs.AIcs.LGarXiv:2210.12283v32022
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
Thao Nguyen, Maithra Raghu, Simon Kornblith
cs.LGarXiv:2010.15327v22020
Deep Reinforcement Learning in Parameterized Action Space
Matthew Hausknecht, Peter Stone
cs.AIcs.LGcs.MAarXiv:1511.04143v52015
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron
Sharan Vaswani, Francis Bach, Mark Schmidt
cs.LGstat.MLarXiv:1810.07288v32018
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift
Alekh Agarwal, Sham M. Kakade, Jason D. Lee +1
cs.LGstat.MLarXiv:1908.00261v52019
A Comprehensive Survey on Deep Graph Representation Learning
Wei Ju, Zheng Fang, Yiyang Gu +13
cs.LGcs.AIcs.IRarXiv:2304.05055v32023
An Alternative View: When Does SGD Escape Local Minima?
Robert Kleinberg, Yuanzhi Li, Yang Yuan
cs.LGarXiv:1802.06175v22018
Orthogonal Subspace Learning for Language Model Continual Learning
Xiao Wang, Tianze Chen, Qiming Ge +6
cs.CLcs.LGarXiv:2310.14152v12023
A Method of Moments for Mixture Models and Hidden Markov Models
Animashree Anandkumar, Daniel Hsu, Sham M. Kakade
cs.LGstat.MLarXiv:1203.0683v32012
Wave Physics as an Analog Recurrent Neural Network
Tyler W. Hughes, Ian A. D. Williamson, Momchil Minkov +1
physics.comp-phcs.LGcs.NEarXiv:1904.12831v22019
Model Selection Techniques -- An Overview
Jie Ding, Vahid Tarokh, Yuhong Yang
stat.MLcs.ITcs.LGarXiv:1810.09583v12018
A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges
Maryam Zare, Parham M. Kebria, Abbas Khosravi +1
cs.LGcs.AIcs.ROarXiv:2309.02473v12023
A Theory of Generative ConvNet
Jianwen Xie, Yang Lu, Song-Chun Zhu +1
stat.MLcs.LGarXiv:1602.03264v32016
An Autoencoder Approach to Learning Bilingual Word Representations
Sarath Chandar A P, Stanislas Lauly, Hugo Larochelle +4
cs.CLcs.LGstat.MLarXiv:1402.1454v12014
OpenPrompt: An Open-source Framework for Prompt-learning
Ning Ding, Shengding Hu, Weilin Zhao +4
cs.CLcs.AIcs.LGarXiv:2111.01998v12021
Accelerating Federated Learning via Momentum Gradient Descent
Wei Liu, Li Chen, Yunfei Chen +1
cs.LGstat.MLarXiv:1910.03197v22019
Learning Graph Embedding with Adversarial Training Methods
Shirui Pan, Ruiqi Hu, Sai-fu Fung +3
cs.LGstat.MLarXiv:1901.01250v22019
Interactive Language: Talking to Robots in Real Time
Corey Lynch, Ayzaan Wahid, Jonathan Tompson +5
cs.ROcs.AIcs.LGarXiv:2210.06407v12022
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong, Zhao Song, Prateek Jain +2
cs.LGcs.DSstat.MLarXiv:1706.03175v12017
DeepSense 6G: A Large-Scale Real-World Multi-Modal Sensing and Communication Dataset
Ahmed Alkhateeb, Gouranga Charan, Tawfik Osman +4
eess.SPcs.CVcs.LGarXiv:2211.09769v22022

Machine Learning

Deep learning: a statistical viewpoint

On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes

WikiHow: A Large Scale Text Summarization Dataset

What graph neural networks cannot learn: depth vs width

AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Images

A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning

An exact mapping between the Variational Renormalization Group and Deep Learning

ASD-DiagNet: A hybrid learning approach for detection of Autism Spectrum Disorder using fMRI data

Dual Discriminator Generative Adversarial Nets

Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks

Label-Free Concept Bottleneck Models

Discovering Discrete Latent Topics with Neural Variational Inference

Physics informed deep learning for computational elastodynamics without labeled data

Machine Learning on Graphs: A Model and Comprehensive Taxonomy

An introduction to domain adaptation and transfer learning

Detecting and Preventing Hallucinations in Large Vision Language Models

Aerial Imagery Pile burn detection using Deep Learning: the FLAME dataset

Robustness via curvature regularization, and vice versa

Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection

MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging

Evaluating Large Language Models at Evaluating Instruction Following

Transolver: A Fast Transformer Solver for PDEs on General Geometries

Deep Learning for Environmentally Robust Speech Recognition: An Overview of Recent Developments

Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI

Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges

Understanding the Acceleration Phenomenon via High-Resolution Differential Equations

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Neural Networks with Few Multiplications

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models

Learning Robust Representations via Multi-View Information Bottleneck

Underdamped Langevin MCMC: A non-asymptotic analysis

Learning without Concentration

Learning Sparse Nonparametric DAGs

First-order Methods for Geodesically Convex Optimization

Proximal Newton-type methods for minimizing composite functions

Explanations in Autonomous Driving: A Survey

Reinforcement and Imitation Learning for Diverse Visuomotor Skills

Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice

Analyzing the Behavior of Visual Question Answering Models

Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs

Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth

Deep Reinforcement Learning in Parameterized Action Space

Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron

On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift

A Comprehensive Survey on Deep Graph Representation Learning

An Alternative View: When Does SGD Escape Local Minima?

Orthogonal Subspace Learning for Language Model Continual Learning

A Method of Moments for Mixture Models and Hidden Markov Models

Wave Physics as an Analog Recurrent Neural Network

Model Selection Techniques -- An Overview

A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges

A Theory of Generative ConvNet

An Autoencoder Approach to Learning Bilingual Word Representations

OpenPrompt: An Open-source Framework for Prompt-learning

Accelerating Federated Learning via Momentum Gradient Descent

Learning Graph Embedding with Adversarial Training Methods

Interactive Language: Talking to Robots in Real Time

Recovery Guarantees for One-hidden-layer Neural Networks

DeepSense 6G: A Large-Scale Real-World Multi-Modal Sensing and Communication Dataset