Machine Learning (stat)

Papers filed under stat.ML 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)

5,941 to 6,000 of 6,790

Reinforcement Learning with Augmented Data
Michael Laskin, Kimin Lee, Adam Stooke +3
cs.LGstat.MLarXiv:2004.14990v52020
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism
Levi McClenny, Ulisses Braga-Neto
cs.LGstat.MLarXiv:2009.04544v52020
Joint Optimization Framework for Learning with Noisy Labels
Daiki Tanaka, Daiki Ikami, Toshihiko Yamasaki +1
cs.CVcs.LGstat.MLarXiv:1803.11364v12018
Deep Learning-Based Communication Over the Air
Sebastian Dörner, Sebastian Cammerer, Jakob Hoydis +1
stat.MLcs.ITarXiv:1707.03384v12017
Motifs in Temporal Networks
Ashwin Paranjape, Austin R. Benson, Jure Leskovec
cs.SIphysics.soc-phstat.MLarXiv:1612.09259v12016
Structured Pruning of Deep Convolutional Neural Networks
Sajid Anwar, Kyuyeon Hwang, Wonyong Sung
cs.NEcs.LGstat.MLarXiv:1512.08571v12015
A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress
Saurabh Arora, Prashant Doshi
cs.LGstat.MLarXiv:1806.06877v32018
Multi-Task Learning with Deep Neural Networks: A Survey
Michael Crawshaw
cs.LGcs.CVstat.MLarXiv:2009.09796v12020
The (Un)reliability of saliency methods
Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo +5
stat.MLcs.LGarXiv:1711.00867v12017
Variational Continual Learning
Cuong V. Nguyen, Yingzhen Li, Thang D. Bui +1
stat.MLcs.LGarXiv:1710.10628v32017
Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm
Bjarke Felbo, Alan Mislove, Anders Søgaard +2
stat.MLcs.LGarXiv:1708.00524v22017
Linear Mode Connectivity and the Lottery Ticket Hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy +1
cs.LGcs.NEstat.MLarXiv:1912.05671v42019
Reinforcement Learning for Combinatorial Optimization: A Survey
Nina Mazyavkina, Sergey Sviridov, Sergei Ivanov +1
cs.LGmath.COmath.OCarXiv:2003.03600v32020
code2seq: Generating Sequences from Structured Representations of Code
Uri Alon, Shaked Brody, Omer Levy +1
cs.LGcs.PLstat.MLarXiv:1808.01400v62018
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks
Jiadong Lin, Chuanbiao Song, Kun He +2
cs.LGcs.CRstat.MLarXiv:1908.06281v52019
MMD GAN: Towards Deeper Understanding of Moment Matching Network
Chun-Liang Li, Wei-Cheng Chang, Yu Cheng +2
cs.LGcs.AIstat.MLarXiv:1705.08584v32017
Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function
Peter Richtárik, Martin Takáč
math.OCstat.MLarXiv:1107.2848v12011
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning
Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning +15
cs.LGcs.AIstat.MLarXiv:1807.01281v12018
Random Search and Reproducibility for Neural Architecture Search
Liam Li, Ameet Talwalkar
cs.LGstat.MLarXiv:1902.07638v32019
Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts
Yuxuan Han, Meng-Hao Guo, Zhengning Liu +2
cs.LGstat.MLarXiv:2603.07169v12026
Neural Boltzmann Equations
Jonas Spinner, Jack Shergold
hep-phcs.LGstat.MLarXiv:2608.23022v12026
Balanced Meta-Softmax for Long-Tailed Visual Recognition
Jiawei Ren, Cunjun Yu, Shunan Sheng +4
cs.LGcs.CVstat.MLarXiv:2007.10740v32020
A Survey on Data Collection for Machine Learning: a Big Data -- AI Integration Perspective
Yuji Roh, Geon Heo, Steven Euijong Whang
cs.LGstat.MLarXiv:1811.03402v22018
Credal Large Language Models for Semantic Commitment under Uncertainty
Shireen Kudukkil Manchingal, Sofiia Nikolenko, Fabio Cuzzolin
cs.CLcs.AIcs.LGarXiv:2608.23244v12026
Sum-Product Networks: A New Deep Architecture
Hoifung Poon, Pedro Domingos
cs.LGcs.AIstat.MLarXiv:1202.3732v12012
Modern hierarchical, agglomerative clustering algorithms
Daniel Müllner
stat.MLcs.DSarXiv:1109.2378v12011
A Note on the Inception Score
Shane Barratt, Rishi Sharma
stat.MLcs.LGarXiv:1801.01973v22018
Tunability: Importance of Hyperparameters of Machine Learning Algorithms
Philipp Probst, Bernd Bischl, Anne-Laure Boulesteix
stat.MLarXiv:1802.09596v32018
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Yarin Gal, Zoubin Ghahramani
stat.MLcs.LGarXiv:1506.02158v62015
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
Andrew Gordon Wilson, Pavel Izmailov
cs.LGstat.MLarXiv:2002.08791v42020
cGANs with Projection Discriminator
Takeru Miyato, Masanori Koyama
cs.LGcs.CVstat.MLarXiv:1802.05637v22018
Learning Scheduling Algorithms for Data Processing Clusters
Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan +2
cs.LGstat.MLarXiv:1810.01963v42018
Doubly Robust Policy Evaluation and Learning
Miroslav Dudik, John Langford, Lihong Li
cs.LGcs.AIcs.ROarXiv:1103.4601v22011
End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks
Richard Cheng, Gabor Orosz, Richard M. Murray +1
cs.LGeess.SYstat.MLarXiv:1903.08792v12019
NAS-Bench-101: Towards Reproducible Neural Architecture Search
Chris Ying, Aaron Klein, Esteban Real +3
cs.LGstat.MLarXiv:1902.09635v22019
Multi-task Sequence to Sequence Learning
Minh-Thang Luong, Quoc V. Le, Ilya Sutskever +2
cs.LGcs.CLstat.MLarXiv:1511.06114v42015
AttGAN: Facial Attribute Editing by Only Changing What You Want
Zhenliang He, Wangmeng Zuo, Meina Kan +2
cs.CVstat.MLarXiv:1711.10678v32017
Automatic Differentiation Variational Inference
Alp Kucukelbir, Dustin Tran, Rajesh Ranganath +2
stat.MLcs.AIcs.LGarXiv:1603.00788v12016
Fast Computation of Wasserstein Barycenters
Marco Cuturi, Arnaud Doucet
stat.MLarXiv:1310.4375v32013
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker
James H Cole, Rudra PK Poudel, Dimosthenis Tsagkrasoulis +4
stat.MLcs.CVcs.LGarXiv:1612.02572v12016
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
Kate Rakelly, Aurick Zhou, Deirdre Quillen +2
cs.LGcs.AIstat.MLarXiv:1903.08254v12019
MOReL : Model-Based Offline Reinforcement Learning
Rahul Kidambi, Aravind Rajeswaran, Praneeth Netrapalli +1
cs.LGcs.AIstat.MLarXiv:2005.05951v32020
CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data
Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau +4
cs.CLcs.IRcs.LGarXiv:1911.00359v22019
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks, Kimin Lee, Mantas Mazeika
cs.LGcs.CVstat.MLarXiv:1901.09960v52019
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
Hongyi Wang, Kartik Sreenivasan, Shashank Rajput +5
cs.LGcs.CRcs.DCarXiv:2007.05084v12020
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack
Jianbo Chen, Michael I. Jordan, Martin J. Wainwright
cs.LGcs.CRmath.OCarXiv:1904.02144v52019
Contrastive Clustering
Yunfan Li, Peng Hu, Zitao Liu +3
cs.LGcs.CVstat.MLarXiv:2009.09687v12020
Transfer learning enhanced physics informed neural network for phase-field modeling of fracture
Somdatta Goswami, Cosmin Anitescu, Souvik Chakraborty +1
stat.MLcs.LGarXiv:1907.02531v12019
An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists
Frédéric Chazal, Bertrand Michel
math.STcs.LGmath.ATarXiv:1710.04019v22017
Likelihood Ratios for Out-of-Distribution Detection
Jie Ren, Peter J. Liu, Emily Fertig +5
stat.MLcs.LGarXiv:1906.02845v22019
Bridging Theory and Algorithm for Domain Adaptation
Yuchen Zhang, Tianle Liu, Mingsheng Long +1
cs.LGstat.MLarXiv:1904.05801v22019
A Commutator Framework for Selective Spectral Alignment in Deep Neural Networks
Kaj Nyström
stat.MLcs.LGarXiv:2608.22910v12026
Meta-Learning: A Survey
Joaquin Vanschoren
cs.LGstat.MLarXiv:1810.03548v12018
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs
Han Liu, John Lafferty, Larry Wasserman
stat.MLarXiv:0903.0649v12009
iDLG: Improved Deep Leakage from Gradients
Bo Zhao, Konda Reddy Mopuri, Hakan Bilen
cs.LGstat.MLarXiv:2001.02610v12020
MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal +1
cs.LGcs.CVcs.ROarXiv:1910.05449v12019
Time Series Data Augmentation for Deep Learning: A Survey
Qingsong Wen, Liang Sun, Fan Yang +4
cs.LGeess.SPstat.MLarXiv:2002.12478v42020
Learning Representations for Counterfactual Inference
Fredrik D. Johansson, Uri Shalit, David Sontag
stat.MLcs.AIcs.LGarXiv:1605.03661v32016
Variational Autoencoder for Deep Learning of Images, Labels and Captions
Yunchen Pu, Zhe Gan, Ricardo Henao +4
stat.MLcs.LGarXiv:1609.08976v12016
Pruning neural networks without any data by iteratively conserving synaptic flow
Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins +1
cs.LGcond-mat.dis-nncs.CVarXiv:2006.05467v32020

Machine Learning (stat)

Reinforcement Learning with Augmented Data

Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism

Joint Optimization Framework for Learning with Noisy Labels

Deep Learning-Based Communication Over the Air

Motifs in Temporal Networks

Structured Pruning of Deep Convolutional Neural Networks

A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress

Multi-Task Learning with Deep Neural Networks: A Survey

The (Un)reliability of saliency methods

Variational Continual Learning

Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

Linear Mode Connectivity and the Lottery Ticket Hypothesis

Reinforcement Learning for Combinatorial Optimization: A Survey

code2seq: Generating Sequences from Structured Representations of Code

Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks

MMD GAN: Towards Deeper Understanding of Moment Matching Network

Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning

Random Search and Reproducibility for Neural Architecture Search

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

Neural Boltzmann Equations

Balanced Meta-Softmax for Long-Tailed Visual Recognition

A Survey on Data Collection for Machine Learning: a Big Data -- AI Integration Perspective

Credal Large Language Models for Semantic Commitment under Uncertainty

Sum-Product Networks: A New Deep Architecture

Modern hierarchical, agglomerative clustering algorithms

A Note on the Inception Score

Tunability: Importance of Hyperparameters of Machine Learning Algorithms

Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference

Bayesian Deep Learning and a Probabilistic Perspective of Generalization

cGANs with Projection Discriminator

Learning Scheduling Algorithms for Data Processing Clusters

Doubly Robust Policy Evaluation and Learning

End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks

NAS-Bench-101: Towards Reproducible Neural Architecture Search

Multi-task Sequence to Sequence Learning

AttGAN: Facial Attribute Editing by Only Changing What You Want

Automatic Differentiation Variational Inference

Fast Computation of Wasserstein Barycenters

Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker

Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables

MOReL : Model-Based Offline Reinforcement Learning

CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data

Using Pre-Training Can Improve Model Robustness and Uncertainty

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning

HopSkipJumpAttack: A Query-Efficient Decision-Based Attack

Contrastive Clustering

Transfer learning enhanced physics informed neural network for phase-field modeling of fracture

An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists

Likelihood Ratios for Out-of-Distribution Detection

Bridging Theory and Algorithm for Domain Adaptation

A Commutator Framework for Selective Spectral Alignment in Deep Neural Networks

Meta-Learning: A Survey

The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs

iDLG: Improved Deep Leakage from Gradients

MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction

Time Series Data Augmentation for Deep Learning: A Survey

Learning Representations for Counterfactual Inference

Variational Autoencoder for Deep Learning of Images, Labels and Captions

Pruning neural networks without any data by iteratively conserving synaptic flow