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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3,541 to 3,600 of 6,785

STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems
Jiani Zhang, Xingjian Shi, Shenglin Zhao +1
cs.IRcs.LGcs.SIarXiv:1905.13129v12019
Distributed Coordinate Descent Method for Learning with Big Data
Peter Richtárik, Martin Takáč
stat.MLcs.DCcs.LGarXiv:1310.2059v12013
Stacked What-Where Auto-encoders
Junbo Zhao, Michael Mathieu, Ross Goroshin +1
stat.MLcs.LGcs.NEarXiv:1506.02351v82015
Zero-shot Knowledge Transfer via Adversarial Belief Matching
Paul Micaelli, Amos Storkey
cs.LGstat.MLarXiv:1905.09768v42019
Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolò Fusi
cs.LGstat.MLarXiv:2002.02923v12020
Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles
Dylan J. Foster, Alexander Rakhlin
cs.LGmath.STstat.MLarXiv:2002.04926v22020
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms
Chi Jin, Qinghua Liu, Sobhan Miryoosefi
cs.LGcs.AIstat.MLarXiv:2102.00815v42021
WACSF - Weighted Atom-Centered Symmetry Functions as Descriptors in Machine Learning Potentials
Michael Gastegger, Ludwig Schwiedrzik, Marius Bittermann +2
physics.chem-phstat.MLarXiv:1712.05861v12017
A Review of Reinforcement Learning for Autonomous Building Energy Management
Karl Mason, Santiago Grijalva
cs.LGeess.SYstat.MLarXiv:1903.05196v22019
Robust Federated Learning in a Heterogeneous Environment
Avishek Ghosh, Justin Hong, Dong Yin +1
cs.LGstat.MLarXiv:1906.06629v22019
On the Complexity Analysis of Randomized Block-Coordinate Descent Methods
Zhaosong Lu, Lin Xiao
math.OCcs.LGmath.NAarXiv:1305.4723v12013
Actions Speak Louder Than Goals: Valuing Player Actions in Soccer
Tom Decroos, Lotte Bransen, Jan Van Haaren +1
stat.APstat.MLarXiv:1802.07127v22018
AnomalyDAE: Dual autoencoder for anomaly detection on attributed networks
Haoyi Fan, Fengbin Zhang, Zuoyong Li
cs.LGstat.MLarXiv:2002.03665v22020
Fairness in Deep Learning: A Computational Perspective
Mengnan Du, Fan Yang, Na Zou +1
cs.LGcs.AIcs.CYarXiv:1908.08843v22019
Learned Video Compression
Oren Rippel, Sanjay Nair, Carissa Lew +3
eess.IVcs.CVcs.LGarXiv:1811.06981v12018
Automated Machine Learning: From Principles to Practices
Zhenqian Shen, Yongqi Zhang, Lanning Wei +2
cs.AIcs.LGstat.MLarXiv:1810.13306v52018
Bayesian Nonparametric Inference of Switching Linear Dynamical Systems
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan +1
stat.MEstat.MLarXiv:1003.3829v12010
Stability Properties of Graph Neural Networks
Fernando Gama, Joan Bruna, Alejandro Ribeiro
cs.LGstat.MLarXiv:1905.04497v52019
Multiscale Deep Equilibrium Models
Shaojie Bai, Vladlen Koltun, J. Zico Kolter
cs.LGcs.CVstat.MLarXiv:2006.08656v22020
The role of parameter Jacobians in the stability of network outputs
Halyun Jeong, Palle E. T. Jorgensen, Hyun-Kyoung Kwon +2
math.FAstat.MLarXiv:2608.27748v12026
Online Control with Adversarial Disturbances
Naman Agarwal, Brian Bullins, Elad Hazan +2
cs.LGeess.SYmath.OCarXiv:1902.08721v12019
Bayesian graph convolutional neural networks for semi-supervised classification
Yingxue Zhang, Soumyasundar Pal, Mark Coates +1
stat.MLcs.LGarXiv:1811.11103v12018
Trend Filtering on Graphs
Yu-Xiang Wang, James Sharpnack, Alex Smola +1
stat.MLcs.AIcs.LGarXiv:1410.7690v52014
Constrained Reinforcement Learning Has Zero Duality Gap
Santiago Paternain, Luiz F. O. Chamon, Miguel Calvo-Fullana +1
cs.LGmath.OCstat.MLarXiv:1910.13393v12019
Measuring Sample Quality with Kernels
Jackson Gorham, Lester Mackey
stat.MLcs.LGarXiv:1703.01717v92017
Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval
Yuxin Chen, Yuejie Chi, Jianqing Fan +1
stat.MLcs.ITcs.LGarXiv:1803.07726v22018
A Clarification of the Nuances in the Fairness Metrics Landscape
Alessandro Castelnovo, Riccardo Crupi, Greta Greco +3
cs.LGcs.CYstat.MLarXiv:2106.00467v42021
Assessing Social and Intersectional Biases in Contextualized Word Representations
Yi Chern Tan, L. Elisa Celis
cs.CLcs.AIcs.CYarXiv:1911.01485v12019
Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling
Qian Wang, Toby P. Breckon
cs.LGcs.CVcs.MMarXiv:1911.07982v12019
Memory Efficient Experience Replay for Streaming Learning
Tyler L. Hayes, Nathan D. Cahill, Christopher Kanan
cs.LGcs.AIstat.MLarXiv:1809.05922v22018
Clustering with Deep Learning: Taxonomy and New Methods
Elie Aljalbout, Vladimir Golkov, Yawar Siddiqui +2
cs.LGcs.AIcs.CVarXiv:1801.07648v22018
Transformers as Algorithms: Generalization and Stability in In-context Learning
Yingcong Li, M. Emrullah Ildiz, Dimitris Papailiopoulos +1
cs.LGcs.CLstat.MLarXiv:2301.07067v22023
Adversarial Attacks Against Medical Deep Learning Systems
Samuel G. Finlayson, Hyung Won Chung, Isaac S. Kohane +1
cs.CRcs.CYcs.LGarXiv:1804.05296v32018
Cross-conformal predictors
Vladimir Vovk
stat.MLcs.LGarXiv:1208.0806v12012
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution
Cong Ma, Kaizheng Wang, Yuejie Chi +1
cs.LGcs.ITmath.OCarXiv:1711.10467v32017
Maximum Principle Based Algorithms for Deep Learning
Qianxiao Li, Long Chen, Cheng Tai +1
cs.LGstat.MLarXiv:1710.09513v42017
Theoretical Foundations of Latent Posterior Factors: Formal Guarantees for Multi-Evidence Reasoning
Aliyu Agboola Alege
cs.AIcs.ITcs.LGarXiv:2603.15674v22026
Abstract Syntax Networks for Code Generation and Semantic Parsing
Maxim Rabinovich, Mitchell Stern, Dan Klein
cs.CLcs.AIcs.LGarXiv:1704.07535v12017
Deep Fried Convnets
Zichao Yang, Marcin Moczulski, Misha Denil +4
cs.LGcs.NEstat.MLarXiv:1412.7149v42014
Learning from History for Byzantine Robust Optimization
Sai Praneeth Karimireddy, Lie He, Martin Jaggi
cs.LGcs.DCmath.OCarXiv:2012.10333v32020
Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers
Apoorv Vyas, Nataraj Jammalamadaka, Xia Zhu +3
cs.LGcs.CVstat.MLarXiv:1809.03576v12018
Multi-Agent Generative Adversarial Imitation Learning
Jiaming Song, Hongyu Ren, Dorsa Sadigh +1
cs.LGcs.AIcs.MAarXiv:1807.09936v12018
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
Juho Lee, Yoonho Lee, Jungtaek Kim +3
cs.LGstat.MLarXiv:1810.00825v32018
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
Anastasios N. Angelopoulos, Stephen Bates, Emmanuel J. Candès +2
cs.LGcs.AIcs.CVarXiv:2110.01052v52021
Weight Agnostic Neural Networks
Adam Gaier, David Ha
cs.LGcs.NEstat.MLarXiv:1906.04358v22019
A Linearly-Convergent Stochastic L-BFGS Algorithm
Philipp Moritz, Robert Nishihara, Michael I. Jordan
math.OCcs.LGmath.NAarXiv:1508.02087v22015
META-DES: A Dynamic Ensemble Selection Framework using Meta-Learning
Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti +1
cs.LGcs.AIstat.MLarXiv:1810.01270v12018
Accounting for Variance in Machine Learning Benchmarks
Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi +14
cs.LGstat.MLarXiv:2103.03098v12021
Robust model-based clustering via mixtures of multivariate pseudo-Voigt distributions
Babak F. Dehkordi, Jeffrey L. Andrews, Andrew Jirasek
stat.MEstat.MLarXiv:2608.27606v12026
Learning One-hidden-layer Neural Networks with Landscape Design
Rong Ge, Jason D. Lee, Tengyu Ma
cs.LGcs.DSmath.OCarXiv:1711.00501v22017
Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning
Xuan Wang, Yu Zhang, Xiang Ren +5
cs.IRcs.CLstat.MLarXiv:1801.09851v42018
Analysis of Langevin Monte Carlo via convex optimization
Alain Durmus, Szymon Majewski, Błażej Miasojedow
stat.COstat.MLarXiv:1802.09188v22018
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression
Tim Salimans, David A. Knowles
stat.COcs.CVstat.MLarXiv:1206.6679v62012
A Simple and Effective Model-Based Variable Importance Measure
Brandon M. Greenwell, Bradley C. Boehmke, Andrew J. McCarthy
stat.MLcs.LGarXiv:1805.04755v12018
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
Minhao Cheng, Simranjit Singh, Patrick Chen +3
cs.LGstat.MLarXiv:1909.10773v32019
Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods
E. David, S. Madec, P. Sadeghi-Tehran +14
cs.CVcs.LGstat.MLarXiv:2005.02162v22020
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
Ronen Basri, David Jacobs, Yoni Kasten +1
cs.LGeess.SPstat.MLarXiv:1906.00425v32019
Semi-Amortized Variational Autoencoders
Yoon Kim, Sam Wiseman, Andrew C. Miller +2
stat.MLcs.CLcs.LGarXiv:1802.02550v72018
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes
James Requeima, Jonathan Gordon, John Bronskill +2
stat.MLcs.LGarXiv:1906.07697v22019
Input Warping for Bayesian Optimization of Non-stationary Functions
Jasper Snoek, Kevin Swersky, Richard S. Zemel +1
stat.MLcs.LGarXiv:1402.0929v32014

Machine Learning (stat)

STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems

Distributed Coordinate Descent Method for Learning with Big Data

Stacked What-Where Auto-encoders

Zero-shot Knowledge Transfer via Adversarial Belief Matching

Geometric Dataset Distances via Optimal Transport

Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles

Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms

WACSF - Weighted Atom-Centered Symmetry Functions as Descriptors in Machine Learning Potentials

A Review of Reinforcement Learning for Autonomous Building Energy Management

Robust Federated Learning in a Heterogeneous Environment

On the Complexity Analysis of Randomized Block-Coordinate Descent Methods

Actions Speak Louder Than Goals: Valuing Player Actions in Soccer

AnomalyDAE: Dual autoencoder for anomaly detection on attributed networks

Fairness in Deep Learning: A Computational Perspective

Learned Video Compression

Automated Machine Learning: From Principles to Practices

Bayesian Nonparametric Inference of Switching Linear Dynamical Systems

Stability Properties of Graph Neural Networks

Multiscale Deep Equilibrium Models

The role of parameter Jacobians in the stability of network outputs

Online Control with Adversarial Disturbances

Bayesian graph convolutional neural networks for semi-supervised classification

Trend Filtering on Graphs

Constrained Reinforcement Learning Has Zero Duality Gap

Measuring Sample Quality with Kernels

Gradient Descent with Random Initialization: Fast Global Convergence for Nonconvex Phase Retrieval

A Clarification of the Nuances in the Fairness Metrics Landscape

Assessing Social and Intersectional Biases in Contextualized Word Representations

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

Memory Efficient Experience Replay for Streaming Learning

Clustering with Deep Learning: Taxonomy and New Methods

Transformers as Algorithms: Generalization and Stability in In-context Learning

Adversarial Attacks Against Medical Deep Learning Systems

Cross-conformal predictors

Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution

Maximum Principle Based Algorithms for Deep Learning

Theoretical Foundations of Latent Posterior Factors: Formal Guarantees for Multi-Evidence Reasoning

Abstract Syntax Networks for Code Generation and Semantic Parsing

Deep Fried Convnets

Learning from History for Byzantine Robust Optimization

Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers

Multi-Agent Generative Adversarial Imitation Learning

Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks

Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

Weight Agnostic Neural Networks

A Linearly-Convergent Stochastic L-BFGS Algorithm

META-DES: A Dynamic Ensemble Selection Framework using Meta-Learning

Accounting for Variance in Machine Learning Benchmarks

Robust model-based clustering via mixtures of multivariate pseudo-Voigt distributions

Learning One-hidden-layer Neural Networks with Landscape Design

Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning

Analysis of Langevin Monte Carlo via convex optimization

Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression

A Simple and Effective Model-Based Variable Importance Measure

Sign-OPT: A Query-Efficient Hard-label Adversarial Attack

Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods

The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies

Semi-Amortized Variational Autoencoders

Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes

Input Warping for Bayesian Optimization of Non-stationary Functions