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.

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8,221 to 8,280 of 9,699

The Why and How of Nonnegative Matrix Factorization
Nicolas Gillis
stat.MLcs.IRcs.LGarXiv:1401.5226v22014
Acquisition of Chess Knowledge in AlphaZero
Thomas McGrath, Andrei Kapishnikov, Nenad Tomašev +5
cs.AIstat.MLarXiv:2111.09259v32021
Priors in Bayesian Deep Learning: A Review
Vincent Fortuin
stat.MLcs.LGarXiv:2105.06868v32021
Interpretable Fundus Image Classification via Ring-Based Retinal Vasculature Features
Xiaoyan Li, Shixin Xu, Arvind Gupta +1
cs.CVstat.MLarXiv:2608.24723v12026
Optimal Exploration-Exploitation in a Multi-Armed-Bandit Problem with Non-stationary Rewards
Omar Besbes, Yonatan Gur, Assaf Zeevi
cs.LGmath.OCmath.PRarXiv:1405.3316v22014
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image
Danny Driess, Jung-Su Ha, Marc Toussaint
cs.LGcs.AIcs.CVarXiv:2006.05398v12020
Discrete Graph Structure Learning for Forecasting Multiple Time Series
Chao Shang, Jie Chen, Jinbo Bi
cs.LGstat.MLarXiv:2101.06861v32021
Reducing Noise in GAN Training with Variance Reduced Extragradient
Tatjana Chavdarova, Gauthier Gidel, François Fleuret +1
stat.MLcs.LGmath.OCarXiv:1904.08598v32019
Unifying Count-Based Exploration and Intrinsic Motivation
Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski +3
cs.AIcs.LGstat.MLarXiv:1606.01868v22016
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Maithra Raghu, Justin Gilmer, Jason Yosinski +1
stat.MLcs.LGarXiv:1706.05806v22017
Federated Forest
Yang Liu, Yingting Liu, Zhijie Liu +3
cs.LGstat.MLarXiv:1905.10053v12019
Achieving Fairness in the Stochastic Multi-armed Bandit Problem
Vishakha Patil, Ganesh Ghalme, Vineet Nair +1
cs.LGstat.MLarXiv:1907.10516v22019
On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon, Eran Yahav
cs.LGstat.MLarXiv:2006.05205v42020
Bayesian Nonparametric Hidden Semi-Markov Models
Matthew J. Johnson, Alan S. Willsky
stat.MEstat.APstat.MLarXiv:1203.1365v22012
Neural Relational Inference for Interacting Systems
Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang +2
stat.MLcs.LGarXiv:1802.04687v22018
Neural Models for Documents with Metadata
Dallas Card, Chenhao Tan, Noah A. Smith
stat.MLcs.CLarXiv:1705.09296v22017
Reinforcement Learning with a Corrupted Reward Channel
Tom Everitt, Victoria Krakovna, Laurent Orseau +2
cs.AIcs.LGstat.MLarXiv:1705.08417v22017
Towards More Practical Adversarial Attacks on Graph Neural Networks
Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei
cs.LGstat.MLarXiv:2006.05057v32020
Training Quantized Nets: A Deeper Understanding
Hao Li, Soham De, Zheng Xu +3
cs.LGcs.CVstat.MLarXiv:1706.02379v32017
Drug discovery with explainable artificial intelligence
José Jiménez-Luna, Francesca Grisoni, Gisbert Schneider
cs.AIcs.LGstat.MLarXiv:2007.00523v22020
Neural ODEs with stochastic vector field mixtures
Niall Twomey, Michał Kozłowski, Raúl Santos-Rodríguez
cs.LGstat.MLarXiv:1905.09905v12019
Federated Learning with Matched Averaging
Hongyi Wang, Mikhail Yurochkin, Yuekai Sun +2
cs.LGstat.MLarXiv:2002.06440v12020
Structured Variable Selection with Sparsity-Inducing Norms
Rodolphe Jenatton, Jean-Yves Audibert, Francis Bach
stat.MLarXiv:0904.3523v32009
Fast Variational Inference in the Conjugate Exponential Family
James Hensman, Magnus Rattray, Neil D. Lawrence
cs.LGstat.MLarXiv:1206.5162v22012
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Marius Mosbach, Maksym Andriushchenko, Dietrich Klakow
cs.LGstat.MLarXiv:2006.04884v32020
Gradient-enhanced kriging for high-dimensional problems
Mohamed Amine Bouhlel, Joaquim R. R. A. Martins
cs.LGstat.MLarXiv:1708.02663v12017
Analyzing and Improving the Training Dynamics of Diffusion Models
Tero Karras, Miika Aittala, Jaakko Lehtinen +3
cs.CVcs.AIcs.LGarXiv:2312.02696v22023
From parcel to continental scale -- A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations
Raphaël d'Andrimont, Astrid Verhegghen, Guido Lemoine +3
stat.MLcs.LGstat.AParXiv:2105.09261v22021
Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning
Divyansh Jhunjhunwala, Advait Gadhikar, Gauri Joshi +1
cs.LGcs.DCstat.MLarXiv:2102.04487v12021
Negative Margin Matters: Understanding Margin in Few-shot Classification
Bin Liu, Yue Cao, Yutong Lin +4
cs.CVcs.LGstat.MLarXiv:2003.12060v12020
End-to-End Learning for Structured Prediction Energy Networks
David Belanger, Bishan Yang, Andrew McCallum
stat.MLcs.LGarXiv:1703.05667v22017
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
Vadim Popov, Ivan Vovk, Vladimir Gogoryan +2
cs.LGcs.CLstat.MLarXiv:2105.06337v22021
Analyzing Inverse Problems with Invertible Neural Networks
Lynton Ardizzone, Jakob Kruse, Sebastian Wirkert +6
cs.LGstat.MLarXiv:1808.04730v32018
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function
Wojciech Tarnowski, Piotr Warchoł, Stanisław Jastrzębski +2
stat.MLcs.LGarXiv:1809.08848v32018
Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control
Kendall Lowrey, Aravind Rajeswaran, Sham Kakade +2
cs.LGcs.AIcs.ROarXiv:1811.01848v32018
Bonsai -- Diverse and Shallow Trees for Extreme Multi-label Classification
Sujay Khandagale, Han Xiao, Rohit Babbar
cs.LGstat.MLarXiv:1904.08249v22019
Lipschitz Continuity in Model-based Reinforcement Learning
Kavosh Asadi, Dipendra Misra, Michael L. Littman
cs.LGcs.AIstat.MLarXiv:1804.07193v32018
Pool-Based Sequential Active Learning for Regression
Dongrui Wu
cs.LGstat.MLarXiv:1805.04735v12018
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks
Matthew D. Zeiler, Rob Fergus
cs.LGcs.NEstat.MLarXiv:1301.3557v12013
Automatic Sleep Stage Scoring with Single-Channel EEG Using Convolutional Neural Networks
Orestis Tsinalis, Paul M. Matthews, Yike Guo +1
stat.MLcs.LGarXiv:1610.01683v12016
Learning Long-Term Dependencies in Irregularly-Sampled Time Series
Mathias Lechner, Ramin Hasani
cs.LGstat.MLarXiv:2006.04418v42020
Rewarding High-Quality Data via Influence Functions
Adam Richardson, Aris Filos-Ratsikas, Boi Faltings
cs.LGcs.AIstat.MLarXiv:1908.11598v12019
Preconditioning Benefits of Spectral Orthogonalization in Muon
Jianhao Ma, Yu Huang, Yuejie Chi +1
cs.LGcs.AImath.OCarXiv:2601.13474v12026
Double/Debiased/Neyman Machine Learning of Treatment Effects
Victor Chernozhukov, Denis Chetverikov, Mert Demirer +3
stat.MLstat.MEarXiv:1701.08687v12017
Continuously Indexed Domain Adaptation
Hao Wang, Hao He, Dina Katabi
cs.LGcs.CVcs.NEarXiv:2007.01807v22020
Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations
Qianxiao Li, Cheng Tai, Weinan E
cs.LGstat.MLarXiv:1811.01558v12018
Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds
Shusen Wang, Alex Gittens, Michael W. Mahoney
cs.LGstat.MLarXiv:1706.02803v42017
Tensor-on-tensor regression
Eric F. Lock
stat.MEstat.MLarXiv:1701.01037v22017
Improving Inference for Neural Image Compression
Yibo Yang, Robert Bamler, Stephan Mandt
eess.IVcs.LGstat.MLarXiv:2006.04240v42020
Learning heat diffusion graphs
Dorina Thanou, Xiaowen Dong, Daniel Kressner +1
cs.LGcs.SIstat.MLarXiv:1611.01456v12016
Investigating the influence of noise and distractors on the interpretation of neural networks
Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller +1
stat.MLcs.LGarXiv:1611.07270v12016
Shorter but not Worse: Frugal Reasoning via Easy Samples as Length Regularizers in Math RLVR
Abdelaziz Bounhar, Hadi Abdine, Evan Dufraisse +5
cs.LGcs.AIstat.MLarXiv:2511.01937v22025
Gap Safe screening rules for sparsity enforcing penalties
Eugene Ndiaye, Olivier Fercoq, Alexandre Gramfort +1
stat.MLcs.LGmath.OCarXiv:1611.05780v42016
Automatic Construction and Natural-Language Description of Nonparametric Regression Models
James Robert Lloyd, David Duvenaud, Roger Grosse +2
stat.MLcs.LGarXiv:1402.4304v32014
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Haim Avron, Vikas Sindhwani, Jiyan Yang +1
stat.MLcs.LGmath.NAarXiv:1412.8293v22014
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
Irina Higgins, Arka Pal, Andrei A. Rusu +6
stat.MLcs.AIcs.LGarXiv:1707.08475v22017
Efficient and Generalizable Archetypal Analysis for Discrete Data
A. Emilie J. Wedenborg, Jesper Løve Hinrich, Morten Mørup
stat.MLcs.LGarXiv:2610.12035v12026
Stochastic Variational Bayesian Inference for a Nonlinear Forward Model
Michael A. Chappell, Martin S. Craig, Mark W. Woolrich
eess.SPstat.APstat.MLarXiv:2007.01675v12020
Efficient L1-Norm Principal-Component Analysis via Bit Flipping
Panos P. Markopoulos, Sandipan Kundu, Shubham Chamadia +1
cs.DScs.LGstat.MLarXiv:1610.01959v12016
Deep Transfer Network with Joint Distribution Adaptation: A New Intelligent Fault Diagnosis Framework for Industry Application
Te Han, Chao Liu, Wenguang Yang +1
cs.LGstat.MLarXiv:1804.07265v12018

Machine Learning (stat)

The Why and How of Nonnegative Matrix Factorization

Acquisition of Chess Knowledge in AlphaZero

Priors in Bayesian Deep Learning: A Review

Interpretable Fundus Image Classification via Ring-Based Retinal Vasculature Features

Optimal Exploration-Exploitation in a Multi-Armed-Bandit Problem with Non-stationary Rewards

Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image

Discrete Graph Structure Learning for Forecasting Multiple Time Series

Reducing Noise in GAN Training with Variance Reduced Extragradient

Unifying Count-Based Exploration and Intrinsic Motivation

SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability

Federated Forest

Achieving Fairness in the Stochastic Multi-armed Bandit Problem

On the Bottleneck of Graph Neural Networks and its Practical Implications

Bayesian Nonparametric Hidden Semi-Markov Models

Neural Relational Inference for Interacting Systems

Neural Models for Documents with Metadata

Reinforcement Learning with a Corrupted Reward Channel

Towards More Practical Adversarial Attacks on Graph Neural Networks

Training Quantized Nets: A Deeper Understanding

Drug discovery with explainable artificial intelligence

Neural ODEs with stochastic vector field mixtures

Federated Learning with Matched Averaging

Structured Variable Selection with Sparsity-Inducing Norms

Fast Variational Inference in the Conjugate Exponential Family

On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines

Gradient-enhanced kriging for high-dimensional problems

Analyzing and Improving the Training Dynamics of Diffusion Models

From parcel to continental scale -- A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations

Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning

Negative Margin Matters: Understanding Margin in Few-shot Classification

End-to-End Learning for Structured Prediction Energy Networks

Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech

Analyzing Inverse Problems with Invertible Neural Networks

Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function

Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control

Bonsai -- Diverse and Shallow Trees for Extreme Multi-label Classification

Lipschitz Continuity in Model-based Reinforcement Learning

Pool-Based Sequential Active Learning for Regression

Stochastic Pooling for Regularization of Deep Convolutional Neural Networks

Automatic Sleep Stage Scoring with Single-Channel EEG Using Convolutional Neural Networks

Learning Long-Term Dependencies in Irregularly-Sampled Time Series

Rewarding High-Quality Data via Influence Functions

Preconditioning Benefits of Spectral Orthogonalization in Muon

Double/Debiased/Neyman Machine Learning of Treatment Effects

Continuously Indexed Domain Adaptation

Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations

Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds

Tensor-on-tensor regression

Improving Inference for Neural Image Compression

Learning heat diffusion graphs

Investigating the influence of noise and distractors on the interpretation of neural networks

Shorter but not Worse: Frugal Reasoning via Easy Samples as Length Regularizers in Math RLVR

Gap Safe screening rules for sparsity enforcing penalties

Automatic Construction and Natural-Language Description of Nonparametric Regression Models

Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels

DARLA: Improving Zero-Shot Transfer in Reinforcement Learning

Efficient and Generalizable Archetypal Analysis for Discrete Data

Stochastic Variational Bayesian Inference for a Nonlinear Forward Model

Efficient L1-Norm Principal-Component Analysis via Bit Flipping

Deep Transfer Network with Joint Distribution Adaptation: A New Intelligent Fault Diagnosis Framework for Industry Application