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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13,381 to 13,440 of 20,205

When Do Neural Nets Outperform Boosted Trees on Tabular Data?
Duncan McElfresh, Sujay Khandagale, Jonathan Valverde +6
cs.LGcs.AIstat.MLarXiv:2305.02997v42023
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play
Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov +3
cs.LGarXiv:1703.05407v52017
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction
Zaixi Zhang, Qi Liu, Hao Wang +2
q-bio.QMcs.AIcs.LGarXiv:2110.00987v22021
Multi-Target Regression via Input Space Expansion: Treating Targets as Inputs
Eleftherios Spyromitros-Xioufis, Grigorios Tsoumakas, William Groves +1
cs.LGarXiv:1211.6581v52012
Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data
Wei-Ning Hsu, Yu Zhang, James Glass
cs.LGcs.CLcs.SDarXiv:1709.07902v12017
Neural Prototype Trees for Interpretable Fine-grained Image Recognition
Meike Nauta, Ron van Bree, Christin Seifert
cs.CVcs.AIcs.LGarXiv:2012.02046v22020
Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild
Weixia Zhang, Kede Ma, Guangtao Zhai +1
cs.CVcs.LGcs.MMarXiv:2005.13983v62020
Application of generative autoencoder in de novo molecular design
Thomas Blaschke, Marcus Olivecrona, Ola Engkvist +2
cs.LGstat.MLarXiv:1711.07839v12017
Disentangled Non-Local Neural Networks
Minghao Yin, Zhuliang Yao, Yue Cao +4
cs.CVcs.CLcs.LGarXiv:2006.06668v22020
Recurrent Neural Networks For Accurate RSSI Indoor Localization
Minh Tu Hoang, Brosnan Yuen, Xiaodai Dong +3
eess.SPcs.LGstat.MLarXiv:1903.11703v22019
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu, Mozhi Zhang, Jingling Li +3
cs.LGcs.AIcs.CVarXiv:2009.11848v52020
iNNvestigate neural networks!
Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer +7
cs.LGstat.MLarXiv:1808.04260v12018
Learning Disentangled Representations with Semi-Supervised Deep Generative Models
N. Siddharth, Brooks Paige, Jan-Willem van de Meent +5
stat.MLcs.AIcs.LGarXiv:1706.00400v22017
The Risks of Invariant Risk Minimization
Elan Rosenfeld, Pradeep Ravikumar, Andrej Risteski
cs.LGcs.AIstat.MLarXiv:2010.05761v22020
FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction
Tongwen Huang, Zhiqi Zhang, Junlin Zhang
cs.LGcs.AIstat.MLarXiv:1905.09433v12019
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects
Oliver T. Unke, Stefan Chmiela, Michael Gastegger +3
physics.chem-phcs.LGarXiv:2105.00304v22021
Learning with a Strong Adversary
Ruitong Huang, Bing Xu, Dale Schuurmans +1
cs.LGarXiv:1511.03034v62015
Dendritic cortical microcircuits approximate the backpropagation algorithm
João Sacramento, Rui Ponte Costa, Yoshua Bengio +1
q-bio.NCcs.LGcs.NEarXiv:1810.11393v12018
AdaRNN: Adaptive Learning and Forecasting of Time Series
Yuntao Du, Jindong Wang, Wenjie Feng +4
cs.LGcs.AIarXiv:2108.04443v22021
PolyGen: An Autoregressive Generative Model of 3D Meshes
Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami +1
cs.GRcs.CVcs.LGarXiv:2002.10880v12020
Stochastic Neural Networks for Hierarchical Reinforcement Learning
Carlos Florensa, Yan Duan, Pieter Abbeel
cs.AIcs.LGcs.NEarXiv:1704.03012v12017
A survey of Bayesian Network structure learning
Neville K. Kitson, Anthony C. Constantinou, Zhigao Guo +2
cs.LGcs.AIarXiv:2109.11415v22021
Poisoning Web-Scale Training Datasets is Practical
Nicholas Carlini, Matthew Jagielski, Christopher A. Choquette-Choo +6
cs.CRcs.LGarXiv:2302.10149v22023
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
Sven Gowal, Chongli Qin, Jonathan Uesato +2
stat.MLcs.AIcs.LGarXiv:2010.03593v32020
Taming the Noise in Reinforcement Learning via Soft Updates
Roy Fox, Ari Pakman, Naftali Tishby
cs.LGcs.ITarXiv:1512.08562v42015
Conditional Computation in Neural Networks for faster models
Emmanuel Bengio, Pierre-Luc Bacon, Joelle Pineau +1
cs.LGarXiv:1511.06297v22015
Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks
Péter Mernyei, Cătălina Cangea
cs.LGcs.SIstat.MLarXiv:2007.02901v22020
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Samuel Horvath, Stefanos Laskaridis, Mario Almeida +3
cs.LGcs.DCarXiv:2102.13451v52021
FACMAC: Factored Multi-Agent Centralised Policy Gradients
Bei Peng, Tabish Rashid, Christian A. Schroeder de Witt +4
cs.LGcs.AIstat.MLarXiv:2003.06709v52020
Robotic Control via Embodied Chain-of-Thought Reasoning
Michał Zawalski, William Chen, Karl Pertsch +3
cs.ROcs.LGarXiv:2407.08693v32024
Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration
Hasan Genc, Seah Kim, Alon Amid +16
cs.DCcs.ARcs.LGarXiv:1911.09925v32019
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections
Ofir Nachum, Yinlam Chow, Bo Dai +1
cs.LGcs.AIstat.MLarXiv:1906.04733v22019
UltraFeedback: Boosting Language Models with Scaled AI Feedback
Ganqu Cui, Lifan Yuan, Ning Ding +9
cs.CLcs.AIcs.LGarXiv:2310.01377v22023
Explaining by Removing: A Unified Framework for Model Explanation
Ian Covert, Scott Lundberg, Su-In Lee
cs.LGstat.MLarXiv:2011.14878v22020
Dimensionality Reduction for k-Means Clustering and Low Rank Approximation
Michael B. Cohen, Sam Elder, Cameron Musco +2
cs.DScs.LGarXiv:1410.6801v32014
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
Maruan Al-Shedivat, Trapit Bansal, Yuri Burda +3
cs.LGcs.AIarXiv:1710.03641v22017
LoRA Learns Less and Forgets Less
Dan Biderman, Jacob Portes, Jose Javier Gonzalez Ortiz +9
cs.LGcs.AIcs.CLarXiv:2405.09673v22024
Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer
Hao Shao, Letian Wang, RuoBing Chen +2
cs.CVcs.AIcs.LGarXiv:2207.14024v52022
Discrete Distribution Estimation under Local Privacy
Peter Kairouz, Keith Bonawitz, Daniel Ramage
stat.MLcs.LGarXiv:1602.07387v32016
CERT: Contrastive Self-supervised Learning for Language Understanding
Hongchao Fang, Sicheng Wang, Meng Zhou +2
cs.CLcs.LGstat.MLarXiv:2005.12766v22020
A Note on Over-Smoothing for Graph Neural Networks
Chen Cai, Yusu Wang
cs.LGstat.MLarXiv:2006.13318v12020
SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation
Yen-Chi Cheng, Hsin-Ying Lee, Sergey Tulyakov +2
cs.CVcs.LGarXiv:2212.04493v22022
State Representation Learning for Control: An Overview
Timothée Lesort, Natalia Díaz-Rodríguez, Jean-François Goudou +1
cs.AIcs.LGstat.MLarXiv:1802.04181v22018
MeshCNN: A Network with an Edge
Rana Hanocka, Amir Hertz, Noa Fish +3
cs.LGcs.CVcs.GRarXiv:1809.05910v22018
Personalize Segment Anything Model with One Shot
Renrui Zhang, Zhengkai Jiang, Ziyu Guo +6
cs.CVcs.AIcs.CLarXiv:2305.03048v22023
Efficient training of physics-informed neural networks via importance sampling
Mohammad Amin Nabian, Rini Jasmine Gladstone, Hadi Meidani
cs.LGmath.APmath.NAarXiv:2104.12325v12021
Document Embedding with Paragraph Vectors
Andrew M. Dai, Christopher Olah, Quoc V. Le
cs.CLcs.AIcs.LGarXiv:1507.07998v12015
Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character Models
Minh-Thang Luong, Christopher D. Manning
cs.CLcs.LGarXiv:1604.00788v22016
Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?
Peter Hase, Mohit Bansal
cs.CLcs.AIcs.LGarXiv:2005.01831v12020
A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting
Jiawei Zhu, Yujiao Song, Ling Zhao +1
cs.LGstat.MLarXiv:2006.11583v12020
Opponent Modeling in Deep Reinforcement Learning
He He, Jordan Boyd-Graber, Kevin Kwok +1
cs.LGarXiv:1609.05559v12016
A Convex Framework for Fair Regression
Richard Berk, Hoda Heidari, Shahin Jabbari +5
cs.LGstat.MLarXiv:1706.02409v12017
Scalable Methods for 8-bit Training of Neural Networks
Ron Banner, Itay Hubara, Elad Hoffer +1
cs.LGstat.MLarXiv:1805.11046v32018
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem
Muning Wen, Jakub Grudzien Kuba, Runji Lin +4
cs.MAcs.LGarXiv:2205.14953v32022
RealFusion: 360° Reconstruction of Any Object from a Single Image
Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina +1
cs.CVcs.AIcs.LGarXiv:2302.10663v22023
Your Diffusion Model is Secretly a Zero-Shot Classifier
Alexander C. Li, Mihir Prabhudesai, Shivam Duggal +2
cs.LGcs.AIcs.CVarXiv:2303.16203v32023
DeepCAD: A Deep Generative Network for Computer-Aided Design Models
Rundi Wu, Chang Xiao, Changxi Zheng
cs.CVcs.GRcs.LGarXiv:2105.09492v22021
CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
Huichu Zhang, Siyuan Feng, Chang Liu +7
cs.MAcs.LGarXiv:1905.05217v12019
Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting
Zezhi Shao, Zhao Zhang, Fei Wang +1
cs.LGarXiv:2206.09113v22022
DeepCas: an End-to-end Predictor of Information Cascades
Cheng Li, Jiaqi Ma, Xiaoxiao Guo +1
cs.SIcs.LGarXiv:1611.05373v12016

Machine Learning

When Do Neural Nets Outperform Boosted Trees on Tabular Data?

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play

Motif-based Graph Self-Supervised Learning for Molecular Property Prediction

Multi-Target Regression via Input Space Expansion: Treating Targets as Inputs

Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data

Neural Prototype Trees for Interpretable Fine-grained Image Recognition

Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild

Application of generative autoencoder in de novo molecular design

Disentangled Non-Local Neural Networks

Recurrent Neural Networks For Accurate RSSI Indoor Localization

How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks

iNNvestigate neural networks!

Learning Disentangled Representations with Semi-Supervised Deep Generative Models

The Risks of Invariant Risk Minimization

FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction

SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects

Learning with a Strong Adversary

Dendritic cortical microcircuits approximate the backpropagation algorithm

AdaRNN: Adaptive Learning and Forecasting of Time Series

PolyGen: An Autoregressive Generative Model of 3D Meshes

Stochastic Neural Networks for Hierarchical Reinforcement Learning

A survey of Bayesian Network structure learning

Poisoning Web-Scale Training Datasets is Practical

Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples

Taming the Noise in Reinforcement Learning via Soft Updates

Conditional Computation in Neural Networks for faster models

Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout

FACMAC: Factored Multi-Agent Centralised Policy Gradients

Robotic Control via Embodied Chain-of-Thought Reasoning

Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration

DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections

UltraFeedback: Boosting Language Models with Scaled AI Feedback

Explaining by Removing: A Unified Framework for Model Explanation

Dimensionality Reduction for k-Means Clustering and Low Rank Approximation

Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments

LoRA Learns Less and Forgets Less

Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer

Discrete Distribution Estimation under Local Privacy

CERT: Contrastive Self-supervised Learning for Language Understanding

A Note on Over-Smoothing for Graph Neural Networks

SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation

State Representation Learning for Control: An Overview

MeshCNN: A Network with an Edge

Personalize Segment Anything Model with One Shot

Efficient training of physics-informed neural networks via importance sampling

Document Embedding with Paragraph Vectors

Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character Models

Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?

A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting

Opponent Modeling in Deep Reinforcement Learning

A Convex Framework for Fair Regression

Scalable Methods for 8-bit Training of Neural Networks

Multi-Agent Reinforcement Learning is a Sequence Modeling Problem

RealFusion: 360° Reconstruction of Any Object from a Single Image

Your Diffusion Model is Secretly a Zero-Shot Classifier

DeepCAD: A Deep Generative Network for Computer-Aided Design Models

CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

DeepCas: an End-to-end Predictor of Information Cascades