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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6,901 to 6,960 of 9,719

Incremental Few-Shot Learning with Attention Attractor Networks
Mengye Ren, Renjie Liao, Ethan Fetaya +1
cs.LGcs.CVstat.MLarXiv:1810.07218v32018
Online Alternating Direction Method
Huahua Wang, Arindam Banerjee
cs.LGstat.MLarXiv:1206.6448v12012
Global convergence of splitting methods for nonconvex composite optimization
Guoyin Li, Ting Kei Pong
math.OCcs.LGmath.NAarXiv:1407.0753v62014
Generalization and Exploration via Randomized Value Functions
Ian Osband, Benjamin Van Roy, Zheng Wen
stat.MLcs.AIcs.LGarXiv:1402.0635v32014
On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions
Francis Bach
cs.LGmath.NAstat.MLarXiv:1502.06800v22015
Understanding Probabilistic Sparse Gaussian Process Approximations
Matthias Bauer, Mark van der Wilk, Carl Edward Rasmussen
stat.MLarXiv:1606.04820v22016
Deep Joint Source-Channel Coding for Wireless Image Transmission
Eirina Bourtsoulatze, David Burth Kurka, Deniz Gunduz
cs.ITcs.LGeess.SParXiv:1809.01733v42018
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination
Nathan Kallus, Xiaojie Mao, Angela Zhou
stat.MLcs.LGmath.OCarXiv:1906.00285v22019
Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review
Sergey Levine
cs.LGcs.AIcs.ROarXiv:1805.00909v32018
Robust XGBoosting for Regression
Iris Aragón Mladosich, Christophe Croux
cs.LGstat.COstat.MLarXiv:2608.13590v12026
Towards Robust Neural Networks via Random Self-ensemble
Xuanqing Liu, Minhao Cheng, Huan Zhang +1
cs.LGcs.CRstat.MLarXiv:1712.00673v22017
Unlabeled Data Improves Adversarial Robustness
Yair Carmon, Aditi Raghunathan, Ludwig Schmidt +2
stat.MLcs.CVcs.LGarXiv:1905.13736v42019
Deep Transfer Learning for Source Code Modeling
Yasir Hussain, Zhiqiu Huang, Yu Zhou +1
cs.LGcs.NEcs.SEarXiv:1910.05493v22019
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
Daniel S. Brown, Russell Coleman, Ravi Srinivasan +1
cs.LGstat.MLarXiv:2002.09089v42020
A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition
Souhaib Ben Taieb, Gianluca Bontempi, Amir Atiya +1
stat.MLcs.AIcs.LGarXiv:1108.3259v12011
Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly Detection
Andrea Paudice, Luis Muñoz-González, Andras Gyorgy +1
stat.MLcs.CRcs.LGarXiv:1802.03041v12018
Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning
Kimin Lee, Kibok Lee, Jinwoo Shin +1
cs.LGstat.MLarXiv:1910.05396v32019
Implicit Regularization in Deep Matrix Factorization
Sanjeev Arora, Nadav Cohen, Wei Hu +1
cs.LGcs.AIcs.NEarXiv:1905.13655v32019
InstaGAN: Instance-aware Image-to-Image Translation
Sangwoo Mo, Minsu Cho, Jinwoo Shin
cs.LGcs.CVstat.MLarXiv:1812.10889v22018
Robust Synthetic Control
Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen
econ.EMstat.APstat.MLarXiv:1711.06940v12017
Statistical consistency and asymptotic normality for high-dimensional robust M-estimators
Po-Ling Loh
math.STcs.ITstat.MLarXiv:1501.00312v12015
Practical sketching algorithms for low-rank matrix approximation
Joel A. Tropp, Alp Yurtsever, Madeleine Udell +1
math.NAcs.DSstat.COarXiv:1609.00048v22016
Conditional Object-Centric Learning from Video
Thomas Kipf, Gamaleldin F. Elsayed, Aravindh Mahendran +6
cs.CVcs.LGstat.MLarXiv:2111.12594v22021
Generative Adversarial User Model for Reinforcement Learning Based Recommendation System
Xinshi Chen, Shuang Li, Hui Li +3
cs.LGcs.IRstat.MLarXiv:1812.10613v32018
Understanding and Improving Layer Normalization
Jingjing Xu, Xu Sun, Zhiyuan Zhang +2
cs.LGcs.CLstat.MLarXiv:1911.07013v12019
A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting
Pei Du, Jianzhou Wang, Yan Hao +2
cs.LGeess.SPstat.AParXiv:1905.13550v12019
Prior-free and prior-dependent regret bounds for Thompson Sampling
Sébastien Bubeck, Che-Yu Liu
stat.MLcs.LGarXiv:1304.5758v22013
A Probabilistic U-Net for Segmentation of Ambiguous Images
Simon A. A. Kohl, Bernardino Romera-Paredes, Clemens Meyer +6
cs.CVcs.LGcs.NEarXiv:1806.05034v42018
Inductive Relation Prediction by Subgraph Reasoning
Komal K. Teru, Etienne Denis, William L. Hamilton
cs.LGcs.AIstat.MLarXiv:1911.06962v22019
Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness
Sebastian Vollmer, Bilal A. Mateen, Gergo Bohner +15
cs.CYcs.LGstat.AParXiv:1812.10404v12018
Revisiting Membership Inference Under Realistic Assumptions
Bargav Jayaraman, Lingxiao Wang, Katherine Knipmeyer +2
cs.CRcs.LGstat.MLarXiv:2005.10881v52020
Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging
Luis Muñoz-González, Kenneth T. Co, Emil C. Lupu
stat.MLcs.DCcs.LGarXiv:1909.05125v12019
Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective
Shixia Liu, Xiting Wang, Mengchen Liu +1
cs.LGstat.MLarXiv:1702.01226v12017
A Unified Optimism-Agnostic Framework for Linear Bandits over Spherical Action Sets
Arda Güçlü, Subhonmesh Bose, John R. Birge
stat.MLcs.LGarXiv:2609.32149v12026
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets
Benjamin Dupuis, Paul Viallard, George Deligiannidis +1
stat.MLcs.LGarXiv:2404.17442v22024
Addressing Failure Prediction by Learning Model Confidence
Charles Corbière, Nicolas Thome, Avner Bar-Hen +2
cs.CVcs.LGstat.MLarXiv:1910.04851v22019
Generative Models for Effective ML on Private, Decentralized Datasets
Sean Augenstein, H. Brendan McMahan, Daniel Ramage +5
cs.LGstat.MLarXiv:1911.06679v22019
Invariant Risk Minimization
Martin Arjovsky, Léon Bottou, Ishaan Gulrajani +1
stat.MLcs.AIcs.LGarXiv:1907.02893v32019
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Luca Franceschi, Paolo Frasconi, Saverio Salzo +2
stat.MLcs.LGarXiv:1806.04910v22018
Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition
Jinmian Ye, Linnan Wang, Guangxi Li +4
cs.LGstat.MLarXiv:1712.05134v22017
Weak-to-Strong Generalization under Distribution Shifts
Myeongho Jeon, Jan Sobotka, Suhwan Choi +1
cs.LGcs.AIstat.MLarXiv:2510.21332v22025
Bypassing Backdoor Detection Algorithms in Deep Learning
Te Juin Lester Tan, Reza Shokri
cs.LGcs.CRstat.MLarXiv:1905.13409v22019
CycleGAN, a Master of Steganography
Casey Chu, Andrey Zhmoginov, Mark Sandler
cs.CVcs.LGstat.MLarXiv:1712.02950v22017
Explaining the Unique Nature of Individual Gait Patterns with Deep Learning
Fabian Horst, Sebastian Lapuschkin, Wojciech Samek +2
cs.LGstat.MLarXiv:1808.04308v22018
Multi-task Self-Supervised Learning for Human Activity Detection
Aaqib Saeed, Tanir Ozcelebi, Johan Lukkien
cs.LGstat.MLarXiv:1907.11879v12019
Introduction to Online Convex Optimization
Elad Hazan
cs.LGmath.OCstat.MLarXiv:1909.05207v32019
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection
Guansong Pang, Longbing Cao, Ling Chen +1
cs.LGcs.AIcs.DBarXiv:1806.04808v12018
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications
Fanhua Shang, James Cheng, Yuanyuan Liu +2
cs.LGcs.CVmath.OCarXiv:1810.05186v12018
Summaries:한국어
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
Yujun Lin, Song Han, Huizi Mao +2
cs.CVcs.DCcs.LGarXiv:1712.01887v32017
Deep Reinforcement Learning at the Edge of the Statistical Precipice
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro +2
cs.LGcs.AIstat.MEarXiv:2108.13264v42021
To prune, or not to prune: exploring the efficacy of pruning for model compression
Michael Zhu, Suyog Gupta
stat.MLcs.LGarXiv:1710.01878v22017
PathFinder: Joint Decompositions of Linked Multimodal Datasets
Ying-Qiu Zheng, Alex Fung, Stephen M Smith +2
cs.LGeess.IVq-bio.QMarXiv:2608.14951v12026
Distilling a Neural Network Into a Soft Decision Tree
Nicholas Frosst, Geoffrey Hinton
cs.LGcs.AIstat.MLarXiv:1711.09784v12017
Interpretable Counterfactual Explanations Guided by Prototypes
Arnaud Van Looveren, Janis Klaise
cs.LGstat.MLarXiv:1907.02584v22019
Memory Aware Synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny +2
cs.CVcs.AIstat.MLarXiv:1711.09601v42017
A Semi-supervised Graph Attentive Network for Financial Fraud Detection
Daixin Wang, Jianbin Lin, Peng Cui +7
cs.SIcs.CRcs.LGarXiv:2003.01171v12020
Provable Robustness of ReLU networks via Maximization of Linear Regions
Francesco Croce, Maksym Andriushchenko, Matthias Hein
cs.LGstat.MLarXiv:1810.07481v22018
On the Expressive Power of Deep Neural Networks
Maithra Raghu, Ben Poole, Jon Kleinberg +2
stat.MLcs.AIcs.LGarXiv:1606.05336v62016
Automatic depth-based local center clustering via $β$-integrated local depth and adaptive grouping
Siyi Wang, Alexandre Leblanc, Paul D. McNicholas
stat.MEcs.LGstat.MLarXiv:2609.26748v12026
Relief-Based Feature Selection: Introduction and Review
Ryan J. Urbanowicz, Melissa Meeker, William LaCava +2
cs.DScs.LGstat.MLarXiv:1711.08421v22017

Machine Learning (stat)

Incremental Few-Shot Learning with Attention Attractor Networks

Online Alternating Direction Method

Global convergence of splitting methods for nonconvex composite optimization

Generalization and Exploration via Randomized Value Functions

On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions

Understanding Probabilistic Sparse Gaussian Process Approximations

Deep Joint Source-Channel Coding for Wireless Image Transmission

Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination

Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

Robust XGBoosting for Regression

Towards Robust Neural Networks via Random Self-ensemble

Unlabeled Data Improves Adversarial Robustness

Deep Transfer Learning for Source Code Modeling

Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences

A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition

Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly Detection

Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning

Implicit Regularization in Deep Matrix Factorization

InstaGAN: Instance-aware Image-to-Image Translation

Robust Synthetic Control

Statistical consistency and asymptotic normality for high-dimensional robust M-estimators

Practical sketching algorithms for low-rank matrix approximation

Conditional Object-Centric Learning from Video

Generative Adversarial User Model for Reinforcement Learning Based Recommendation System

Understanding and Improving Layer Normalization

A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting

Prior-free and prior-dependent regret bounds for Thompson Sampling

A Probabilistic U-Net for Segmentation of Ambiguous Images

Inductive Relation Prediction by Subgraph Reasoning

Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness

Revisiting Membership Inference Under Realistic Assumptions

Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective

A Unified Optimism-Agnostic Framework for Linear Bandits over Spherical Action Sets

Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets

Addressing Failure Prediction by Learning Model Confidence

Generative Models for Effective ML on Private, Decentralized Datasets

Invariant Risk Minimization

Bilevel Programming for Hyperparameter Optimization and Meta-Learning

Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition

Weak-to-Strong Generalization under Distribution Shifts

Bypassing Backdoor Detection Algorithms in Deep Learning

CycleGAN, a Master of Steganography

Explaining the Unique Nature of Individual Gait Patterns with Deep Learning

Multi-task Self-Supervised Learning for Human Activity Detection

Introduction to Online Convex Optimization

Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection

Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications

Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

Deep Reinforcement Learning at the Edge of the Statistical Precipice

To prune, or not to prune: exploring the efficacy of pruning for model compression

PathFinder: Joint Decompositions of Linked Multimodal Datasets

Distilling a Neural Network Into a Soft Decision Tree

Interpretable Counterfactual Explanations Guided by Prototypes

Memory Aware Synapses: Learning what (not) to forget

A Semi-supervised Graph Attentive Network for Financial Fraud Detection

Provable Robustness of ReLU networks via Maximization of Linear Regions

On the Expressive Power of Deep Neural Networks

Automatic depth-based local center clustering via $β$-integrated local depth and adaptive grouping

Relief-Based Feature Selection: Introduction and Review