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)

541 to 600 of 6,779

A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series
Wenqian Jiang, Cheng Cheng, Beitong Zhou +2
cs.LGstat.MLarXiv:1904.00575v12019
Adversarial Training for Tabular Credit Scoring: A Multi-Attack Robustness Evaluation in P2P Lending
Gijs A. F. Niewzwaag, Marijn G. S. Veth, Manuele Massei +1
cs.LGq-fin.RMstat.MLarXiv:2609.09945v12026
Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN
Hyeungill Lee, Sungyeob Han, Jungwoo Lee
cs.LGstat.MLarXiv:1705.03387v32017
Learning representations of irregular particle-detector geometry with distance-weighted graph networks
Shah Rukh Qasim, Jan Kieseler, Yutaro Iiyama +1
physics.data-ancs.CVcs.LGarXiv:1902.07987v22019
Probabilistic Prediction of Vehicle Semantic Intention and Motion
Yeping Hu, Wei Zhan, Masayoshi Tomizuka
cs.LGstat.MLarXiv:1804.03629v12018
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology
Nima Dehmamy, Albert-László Barabási, Rose Yu
cs.LGphysics.data-anstat.MLarXiv:1907.05008v22019
AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks
Aditya Devarakonda, Maxim Naumov, Michael Garland
cs.LGcs.CVcs.DCarXiv:1712.02029v22017
Importance of Tuning Hyperparameters of Machine Learning Algorithms
Hilde J. P. Weerts, Andreas C. Mueller, Joaquin Vanschoren
cs.LGstat.MLarXiv:2007.07588v12020
Bayesian Generative Active Deep Learning
Toan Tran, Thanh-Toan Do, Ian Reid +1
cs.LGstat.MLarXiv:1904.11643v12019
Information Constraints on Auto-Encoding Variational Bayes
Romain Lopez, Jeffrey Regier, Michael I. Jordan +1
cs.LGq-bio.GNstat.MLarXiv:1805.08672v42018
Community Detection in Degree-Corrected Block Models
Chao Gao, Zongming Ma, Anderson Y. Zhang +1
math.STcs.SIstat.MLarXiv:1607.06993v12016
Smoothed Analysis of Tensor Decompositions
Aditya Bhaskara, Moses Charikar, Ankur Moitra +1
cs.DScs.LGstat.MLarXiv:1311.3651v42013
Efficient Private ERM for Smooth Objectives
Jiaqi Zhang, Kai Zheng, Wenlong Mou +1
cs.LGcs.DSstat.MLarXiv:1703.09947v22017
Muon-C: Operator-Aligned Muon for Convolutional Kernels
Jiaxin Qing, Lexin Li
cs.LGstat.MLarXiv:2609.09676v12026
Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks
Yabo Ni, Dan Ou, Shichen Liu +4
stat.MLcs.LGarXiv:1805.10727v12018
Learning Latent Subspaces in Variational Autoencoders
Jack Klys, Jake Snell, Richard Zemel
cs.LGcs.CVstat.MLarXiv:1812.06190v12018
Adaptive Reward-Poisoning Attacks against Reinforcement Learning
Xuezhou Zhang, Yuzhe Ma, Adish Singla +1
cs.LGcs.AIcs.CRarXiv:2003.12613v22020
Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues
Nihar B. Shah, Sivaraman Balakrishnan, Adityanand Guntuboyina +1
stat.MLcs.ITcs.LGarXiv:1510.05610v42015
On the limits of cross-domain generalization in automated X-ray prediction
Joseph Paul Cohen, Mohammad Hashir, Rupert Brooks +1
eess.IVcs.LGq-bio.QMarXiv:2002.02497v22020
Tensor-Train Weak SINDy: Identifying High-Dimensional Nonlinear Dynamics
Will Houser, Vanja Dukic, David M. Bortz
cs.LGcs.CEstat.MLarXiv:2609.09434v12026
Differentiable Dynamic Programming for Structured Prediction and Attention
Arthur Mensch, Mathieu Blondel
stat.MLcs.LGarXiv:1802.03676v22018
A Fast Distributed Proximal-Gradient Method
Annie I. Chen, Asuman Ozdaglar
cs.DCcs.LGstat.MLarXiv:1210.2289v12012
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization
Roy Frostig, Rong Ge, Sham M. Kakade +1
stat.MLcs.DScs.LGarXiv:1506.07512v12015
Classification of Hand Movements from EEG using a Deep Attention-based LSTM Network
Guangyi Zhang, Vandad Davoodnia, Alireza Sepas-Moghaddam +2
cs.LGeess.SPstat.MLarXiv:1908.02252v22019
Best Practices for Scientific Research on Neural Architecture Search
Marius Lindauer, Frank Hutter
cs.LGstat.MLarXiv:1909.02453v32019
Generalizable Adversarial Training via Spectral Normalization
Farzan Farnia, Jesse M. Zhang, David Tse
cs.LGstat.MLarXiv:1811.07457v12018
Preferential Bayesian Optimization
Javier Gonzalez, Zhenwen Dai, Andreas Damianou +1
stat.MLarXiv:1704.03651v12017
Asynchrony begets Momentum, with an Application to Deep Learning
Ioannis Mitliagkas, Ce Zhang, Stefan Hadjis +1
stat.MLcs.DCcs.LGarXiv:1605.09774v22016
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent
Tian Tong, Cong Ma, Yuejie Chi
cs.LGcs.ITeess.SParXiv:2005.08898v42020
On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks
Maximilian Seitzer, Arash Tavakoli, Dimitrije Antic +1
cs.LGstat.MLarXiv:2203.09168v22022
Deep Learning Reconstruction of Ultra-Short Pulses
Tom Zahavy, Alex Dikopoltsev, Oren Cohen +2
physics.opticscs.AIcs.LGarXiv:1803.06024v12018
Universal Successor Features Approximators
Diana Borsa, André Barreto, John Quan +5
cs.LGcs.AIstat.MLarXiv:1812.07626v12018
Offline Multi-Action Policy Learning: Generalization and Optimization
Zhengyuan Zhou, Susan Athey, Stefan Wager
stat.MLcs.LGecon.EMarXiv:1810.04778v22018
Tilted Empirical Risk Minimization
Tian Li, Ahmad Beirami, Maziar Sanjabi +1
cs.LGcs.ITstat.MLarXiv:2007.01162v22020
Efficient Contextual Bandits in Non-stationary Worlds
Haipeng Luo, Chen-Yu Wei, Alekh Agarwal +1
cs.LGstat.MLarXiv:1708.01799v42017
Theory for Equivariant Quantum Neural Networks
Quynh T. Nguyen, Louis Schatzki, Paolo Braccia +5
quant-phcs.LGstat.MLarXiv:2210.08566v22022
Deep Learning on Small Datasets without Pre-Training using Cosine Loss
Björn Barz, Joachim Denzler
cs.LGcs.CVstat.MLarXiv:1901.09054v22019
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP
Haonan Yu, Sergey Edunov, Yuandong Tian +1
stat.MLcs.AIcs.LGarXiv:1906.02768v32019
Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling
Jacob Menick, Nal Kalchbrenner
cs.CVcs.GRcs.LGarXiv:1812.01608v12018
The Effect of Natural Distribution Shift on Question Answering Models
John Miller, Karl Krauth, Benjamin Recht +1
cs.LGcs.CLstat.MLarXiv:2004.14444v12020
Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data
Matthias Gerstgrasser, Rylan Schaeffer, Apratim Dey +11
cs.LGcs.AIcs.CLarXiv:2404.01413v22024
Directed Information Graphs
Christopher J. Quinn, Negar Kiyavash, Todd P. Coleman
cs.ITcs.AIstat.MLarXiv:1204.2003v22012
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
Vincent Fortuin, Matthias Hüser, Francesco Locatello +2
cs.LGstat.MLarXiv:1806.02199v72018
Agnostic System Identification for Model-Based Reinforcement Learning
Stephane Ross, J. Andrew Bagnell
cs.LGcs.AIeess.SYarXiv:1203.1007v22012
LSCP: Locally Selective Combination in Parallel Outlier Ensembles
Yue Zhao, Zain Nasrullah, Maciej K. Hryniewicki +1
cs.LGcs.IRstat.MLarXiv:1812.01528v22018
Hypothesis Testing Interpretations and Renyi Differential Privacy
Borja Balle, Gilles Barthe, Marco Gaboardi +2
cs.LGstat.MLarXiv:1905.09982v22019
Diagnostic Classification Of Lung Nodules Using 3D Neural Networks
Raunak Dey, Zhongjie Lu, Yi Hong
cs.CVcs.LGstat.MLarXiv:1803.07192v12018
Probabilistic FastText for Multi-Sense Word Embeddings
Ben Athiwaratkun, Andrew Gordon Wilson, Anima Anandkumar
cs.CLcs.AIcs.LGarXiv:1806.02901v12018
Tree Tensor Networks for Generative Modeling
Song Cheng, Lei Wang, Tao Xiang +1
stat.MLcond-mat.stat-mechcs.LGarXiv:1901.02217v12019
ByRDiE: Byzantine-resilient distributed coordinate descent for decentralized learning
Zhixiong Yang, Waheed U. Bajwa
cs.LGcs.DCmath.OCarXiv:1708.08155v42017
ProteinNet: a standardized data set for machine learning of protein structure
Mohammed AlQuraishi
q-bio.BMcs.LGq-bio.QMarXiv:1902.00249v12019
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction
Kwan Ho Ryan Chan, Yaodong Yu, Chong You +3
cs.LGcs.CVcs.ITarXiv:2105.10446v32021
Neuron Shapley: Discovering the Responsible Neurons
Amirata Ghorbani, James Zou
stat.MLcs.CVcs.LGarXiv:2002.09815v32020
Representational Strengths and Limitations of Transformers
Clayton Sanford, Daniel Hsu, Matus Telgarsky
cs.LGstat.MLarXiv:2306.02896v22023
Deep Image Translation with an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection
Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi +4
cs.LGcs.CVeess.IVarXiv:2001.04271v22020
Operator-valued Kernels for Learning from Functional Response Data
Hachem Kadri, Emmanuel Duflos, Philippe Preux +3
cs.LGstat.MLarXiv:1510.08231v32015
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
Gen Li, Yuting Wei, Yuejie Chi +1
cs.LGcs.ITmath.OCarXiv:2005.12900v82020
The Skellam Mechanism for Differentially Private Federated Learning
Naman Agarwal, Peter Kairouz, Ziyu Liu
cs.LGcs.CRcs.DSarXiv:2110.04995v22021
NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search
Arber Zela, Julien Siems, Frank Hutter
cs.LGcs.CVcs.NEarXiv:2001.10422v22020
Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics
Julia Westermayr, Michael Gastegger, Philipp Marquetand
physics.chem-phcs.LGstat.MLarXiv:2002.07264v12020

Machine Learning (stat)

A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series

Adversarial Training for Tabular Credit Scoring: A Multi-Attack Robustness Evaluation in P2P Lending

Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN

Learning representations of irregular particle-detector geometry with distance-weighted graph networks

Probabilistic Prediction of Vehicle Semantic Intention and Motion

Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology

AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks

Importance of Tuning Hyperparameters of Machine Learning Algorithms

Bayesian Generative Active Deep Learning

Information Constraints on Auto-Encoding Variational Bayes

Community Detection in Degree-Corrected Block Models

Smoothed Analysis of Tensor Decompositions

Efficient Private ERM for Smooth Objectives

Muon-C: Operator-Aligned Muon for Convolutional Kernels

Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks

Learning Latent Subspaces in Variational Autoencoders

Adaptive Reward-Poisoning Attacks against Reinforcement Learning

Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues

On the limits of cross-domain generalization in automated X-ray prediction

Tensor-Train Weak SINDy: Identifying High-Dimensional Nonlinear Dynamics

Differentiable Dynamic Programming for Structured Prediction and Attention

A Fast Distributed Proximal-Gradient Method

Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization

Classification of Hand Movements from EEG using a Deep Attention-based LSTM Network

Best Practices for Scientific Research on Neural Architecture Search

Generalizable Adversarial Training via Spectral Normalization

Preferential Bayesian Optimization

Asynchrony begets Momentum, with an Application to Deep Learning

Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent

On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks

Deep Learning Reconstruction of Ultra-Short Pulses

Universal Successor Features Approximators

Offline Multi-Action Policy Learning: Generalization and Optimization

Tilted Empirical Risk Minimization

Efficient Contextual Bandits in Non-stationary Worlds

Theory for Equivariant Quantum Neural Networks

Deep Learning on Small Datasets without Pre-Training using Cosine Loss

Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP

Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling

The Effect of Natural Distribution Shift on Question Answering Models

Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data

Directed Information Graphs

SOM-VAE: Interpretable Discrete Representation Learning on Time Series

Agnostic System Identification for Model-Based Reinforcement Learning

LSCP: Locally Selective Combination in Parallel Outlier Ensembles

Hypothesis Testing Interpretations and Renyi Differential Privacy

Diagnostic Classification Of Lung Nodules Using 3D Neural Networks

Probabilistic FastText for Multi-Sense Word Embeddings

Tree Tensor Networks for Generative Modeling

ByRDiE: Byzantine-resilient distributed coordinate descent for decentralized learning

ProteinNet: a standardized data set for machine learning of protein structure

ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction

Neuron Shapley: Discovering the Responsible Neurons

Representational Strengths and Limitations of Transformers

Deep Image Translation with an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection

Operator-valued Kernels for Learning from Functional Response Data

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model

The Skellam Mechanism for Differentially Private Federated Learning

NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search

Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics