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)

13,441 to 13,500 of 20,219

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
Just Interpolate: Kernel "Ridgeless" Regression Can Generalize
Tengyuan Liang, Alexander Rakhlin
math.STcs.LGstat.MLarXiv:1808.00387v22018
Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck Approach
Jiawei Shao, Yuyi Mao, Jun Zhang
eess.SPcs.LGarXiv:2102.04170v32021
On Completeness-aware Concept-Based Explanations in Deep Neural Networks
Chih-Kuan Yeh, Been Kim, Sercan O. Arik +3
cs.LGstat.MLarXiv:1910.07969v62019
Sparse Networks from Scratch: Faster Training without Losing Performance
Tim Dettmers, Luke Zettlemoyer
cs.LGcs.NEstat.MLarXiv:1907.04840v22019
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters
Hao Zhang, Zeyu Zheng, Shizhen Xu +7
cs.LGcs.CVcs.DCarXiv:1706.03292v12017
GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination
Junyuan Shang, Cao Xiao, Tengfei Ma +2
cs.AIcs.LGstat.MLarXiv:1809.01852v32018
The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials
Ilyes Batatia, Simon Batzner, Dávid Péter Kovács +6
stat.MLcond-mat.mtrl-scics.LGarXiv:2205.06643v22022
Social Biases in NLP Models as Barriers for Persons with Disabilities
Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton +3
cs.CLcs.AIcs.LGarXiv:2005.00813v12020
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning
Eun Seo Jo, Timnit Gebru
cs.LGcs.AIcs.CYarXiv:1912.10389v12019
Pros and Cons of GAN Evaluation Measures: New Developments
Ali Borji
cs.LGcs.AIcs.CVarXiv:2103.09396v32021
Meta-Gradient Reinforcement Learning
Zhongwen Xu, Hado van Hasselt, David Silver
cs.LGcs.AIstat.MLarXiv:1805.09801v12018
Concept Whitening for Interpretable Image Recognition
Zhi Chen, Yijie Bei, Cynthia Rudin
cs.LGcs.AIcs.CVarXiv:2002.01650v52020
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna +3
cs.CVcs.AIcs.CLarXiv:2402.07865v22024
MOSNet: Deep Learning based Objective Assessment for Voice Conversion
Chen-Chou Lo, Szu-Wei Fu, Wen-Chin Huang +4
cs.SDcs.LGeess.ASarXiv:1904.08352v32019
Recent Advances in Convolutional Neural Network Acceleration
Qianru Zhang, Meng Zhang, Tinghuan Chen +3
cs.LGstat.MLarXiv:1807.08596v12018
A Survey on Oversmoothing in Graph Neural Networks
T. Konstantin Rusch, Michael M. Bronstein, Siddhartha Mishra
cs.LGarXiv:2303.10993v12023
Exploiting Cyclic Symmetry in Convolutional Neural Networks
Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu
cs.LGcs.CVcs.NEarXiv:1602.02660v22016
Compacting, Picking and Growing for Unforgetting Continual Learning
Steven C. Y. Hung, Cheng-Hao Tu, Cheng-En Wu +3
cs.LGstat.MLarXiv:1910.06562v32019
Task2Vec: Task Embedding for Meta-Learning
Alessandro Achille, Michael Lam, Rahul Tewari +5
cs.LGcs.AIstat.MLarXiv:1902.03545v12019
Negative Margin Matters: Understanding Margin in Few-shot Classification
Bin Liu, Yue Cao, Yutong Lin +4
cs.CVcs.LGstat.MLarXiv:2003.12060v12020
Approximate Data Deletion from Machine Learning Models
Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri +1
cs.LGstat.MLarXiv:2002.10077v22020
The choice of scaling technique matters for classification performance
Lucas B. V. de Amorim, George D. C. Cavalcanti, Rafael M. O. Cruz
cs.LGarXiv:2212.12343v12022
Meta Learning Shared Hierarchies
Kevin Frans, Jonathan Ho, Xi Chen +2
cs.LGarXiv:1710.09767v12017
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks
Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
cs.CVcs.LGstat.MLarXiv:1802.04034v32018
Whitening Sentence Representations for Better Semantics and Faster Retrieval
Jianlin Su, Jiarun Cao, Weijie Liu +1
cs.CLcs.AIcs.LGarXiv:2103.15316v12021
Structure-Aware Transformer for Graph Representation Learning
Dexiong Chen, Leslie O'Bray, Karsten Borgwardt
stat.MLcs.LGarXiv:2202.03036v32022
PacGAN: The power of two samples in generative adversarial networks
Zinan Lin, Ashish Khetan, Giulia Fanti +1
cs.LGcs.ITstat.MLarXiv:1712.04086v32017
Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach
Minhao Cheng, Thong Le, Pin-Yu Chen +3
cs.LGcs.AIstat.MLarXiv:1807.04457v12018
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
Cunchao Zhu, Muhao Chen, Changjun Fan +2
cs.AIcs.CLcs.LGarXiv:2012.08492v22020
Data Poisoning Attacks on Factorization-Based Collaborative Filtering
Bo Li, Yining Wang, Aarti Singh +1
cs.LGcs.CRcs.IRarXiv:1608.08182v22016
Long Range Language Modeling via Gated State Spaces
Harsh Mehta, Ankit Gupta, Ashok Cutkosky +1
cs.LGcs.CLarXiv:2206.13947v32022
Towards Biologically Plausible Deep Learning
Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein +2
cs.LGarXiv:1502.04156v32015
MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
Ziheng Jiang, Haibin Lin, Yinmin Zhong +29
cs.LGcs.DCarXiv:2402.15627v12024
Addressing Failure Prediction by Learning Model Confidence
Charles Corbière, Nicolas Thome, Avner Bar-Hen +2
cs.CVcs.LGstat.MLarXiv:1910.04851v22019
Dataset Distillation
Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba +1
cs.LGstat.MLarXiv:1811.10959v32018
Large-scale Multi-label Text Classification - Revisiting Neural Networks
Jinseok Nam, Jungi Kim, Eneldo Loza Mencía +2
cs.LGarXiv:1312.5419v32013
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
Yoshua Bengio, Tristan Deleu, Nasim Rahaman +5
cs.LGstat.MLarXiv:1901.10912v22019
Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awareness
Shuo Cheng, Zexiang Xu, Shilin Zhu +4
cs.CVcs.LGcs.ROarXiv:1911.12012v22019
Feature relevance quantification in explainable AI: A causal problem
Dominik Janzing, Lenon Minorics, Patrick Blöbaum
stat.MLcs.LGarXiv:1910.13413v22019
NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking
Daniel Dauner, Marcel Hallgarten, Tianyu Li +9
cs.CVcs.AIcs.LGarXiv:2406.15349v22024
Can language models learn from explanations in context?
Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan +6
cs.CLcs.AIcs.LGarXiv:2204.02329v42022
A Point-of-Prescription Safety-Check System for Adverse Drug Reactions in Rural Bangladeshi Hospitals: A Feasibility Study
Shahir Abdullah
cs.HCcs.LGarXiv:2608.27239v12026
Spatio-Temporal Meta-Graph Learning for Traffic Forecasting
Renhe Jiang, Zhaonan Wang, Jiawei Yong +6
cs.LGcs.AIarXiv:2211.14701v42022
A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models
Chelsea Finn, Paul Christiano, Pieter Abbeel +1
cs.LGcs.AIarXiv:1611.03852v32016
Attribute Prototype Network for Zero-Shot Learning
Wenjia Xu, Yongqin Xian, Jiuniu Wang +2
cs.CVcs.LGarXiv:2008.08290v42020
Generative Semantic Scene Completion
Shi Chen, Weifeng Ge
cs.CVcs.LGcs.ROarXiv:2608.26737v12026

Machine Learning

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

Just Interpolate: Kernel "Ridgeless" Regression Can Generalize

Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck Approach

On Completeness-aware Concept-Based Explanations in Deep Neural Networks

Sparse Networks from Scratch: Faster Training without Losing Performance

Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters

GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination

The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Social Biases in NLP Models as Barriers for Persons with Disabilities

Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning

Pros and Cons of GAN Evaluation Measures: New Developments

Meta-Gradient Reinforcement Learning

Concept Whitening for Interpretable Image Recognition

Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models

MOSNet: Deep Learning based Objective Assessment for Voice Conversion

Recent Advances in Convolutional Neural Network Acceleration

A Survey on Oversmoothing in Graph Neural Networks

Exploiting Cyclic Symmetry in Convolutional Neural Networks

Compacting, Picking and Growing for Unforgetting Continual Learning

Task2Vec: Task Embedding for Meta-Learning

Negative Margin Matters: Understanding Margin in Few-shot Classification

Approximate Data Deletion from Machine Learning Models

The choice of scaling technique matters for classification performance

Meta Learning Shared Hierarchies

Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks

Whitening Sentence Representations for Better Semantics and Faster Retrieval

Structure-Aware Transformer for Graph Representation Learning

PacGAN: The power of two samples in generative adversarial networks

Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach

Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks

Data Poisoning Attacks on Factorization-Based Collaborative Filtering

Long Range Language Modeling via Gated State Spaces

Towards Biologically Plausible Deep Learning

MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs

Addressing Failure Prediction by Learning Model Confidence

Dataset Distillation

Large-scale Multi-label Text Classification - Revisiting Neural Networks

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms

Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awareness

Feature relevance quantification in explainable AI: A causal problem

NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking

Can language models learn from explanations in context?

A Point-of-Prescription Safety-Check System for Adverse Drug Reactions in Rural Bangladeshi Hospitals: A Feasibility Study

Spatio-Temporal Meta-Graph Learning for Traffic Forecasting

A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models

Attribute Prototype Network for Zero-Shot Learning

Generative Semantic Scene Completion