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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8,461 to 8,520 of 9,685

Nonparametric ridge estimation
Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli +1
math.STcs.LGstat.MLarXiv:1212.5156v32012
Finite-Sample Analysis of Proximal Gradient TD Algorithms
Bo Liu, Ji Liu, Mohammad Ghavamzadeh +2
cs.LGstat.MLarXiv:2006.14364v22020
A Multivariate Regression Approach to Association Analysis of Quantitative Trait Network
Seyoung Kim, Kyung-Ah Sohn, Eric P. Xing
stat.MLq-bio.GNq-bio.MNarXiv:0811.2026v12008
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems
Yulong Cao, Chaowei Xiao, Dawei Yang +4
cs.CRcs.CVcs.LGarXiv:1907.05418v12019
An Accurate and Single-Communication Federated Inference Algorithm
Laura Montagnani, Anthony CC Coolen, Marianne A Jonker
stat.MEmath.STstat.COarXiv:2608.27063v12026
Fast Two-Sample Testing with Analytic Representations of Probability Measures
Kacper Chwialkowski, Aaditya Ramdas, Dino Sejdinovic +1
stat.MLarXiv:1506.04725v12015
Sharp Bounds on the Approximation Rates, Metric Entropy, and $n$-widths of Shallow Neural Networks
Jonathan W. Siegel, Jinchao Xu
stat.MLcs.ITcs.LGarXiv:2101.12365v102021
A Closer Look at Invalid Action Masking in Policy Gradient Algorithms
Shengyi Huang, Santiago Ontañón
cs.LGcs.AIstat.MLarXiv:2006.14171v32020
KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics
Guy Revach, Nir Shlezinger, Xiaoyong Ni +3
eess.SPcs.LGstat.MLarXiv:2107.10043v32021
DyNet: The Dynamic Neural Network Toolkit
Graham Neubig, Chris Dyer, Yoav Goldberg +22
stat.MLcs.CLcs.MSarXiv:1701.03980v12017
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
Tejas D. Kulkarni, Karthik R. Narasimhan, Ardavan Saeedi +1
cs.LGcs.AIcs.CVarXiv:1604.06057v22016
Random Vector Functional Link Networks for Function Approximation on Manifolds
Deanna Needell, Aaron A. Nelson, Rayan Saab +2
stat.MLcs.ITcs.LGarXiv:2007.15776v42020
On the Distribution of Penalized Maximum Likelihood Estimators: The LASSO, SCAD, and Thresholding
Benedikt M. Potscher, Hannes Leeb
math.STstat.MEstat.MLarXiv:0711.0660v22007
Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach
Hao-Hsuan Chang, Hao Song, Yang Yi +3
cs.LGstat.MLarXiv:1810.11758v12018
Uniform Race: Parameter-Free Approximate Rejection Sampling
Seiyun Shin, Juhyeong Pang, Kwang-Sung Jun
cs.LGstat.MLarXiv:2609.34639v12026
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit +2
cs.LGcs.IRcs.SEarXiv:1909.09436v32019
A la Carte - Learning Fast Kernels
Zichao Yang, Alexander J. Smola, Le Song +1
cs.LGstat.MLarXiv:1412.6493v12014
Distral: Robust Multitask Reinforcement Learning
Yee Whye Teh, Victor Bapst, Wojciech Marian Czarnecki +5
cs.LGstat.MLarXiv:1707.04175v12017
Deep learning with Elastic Averaging SGD
Sixin Zhang, Anna Choromanska, Yann LeCun
cs.LGstat.MLarXiv:1412.6651v82014
Tolerance-Based Fairness Auditing: Violation Certification and Sensitivity Screening
Jie Tang, Chuanlong Xie, Lixing Zhu
stat.MLcs.LGstat.MEarXiv:2610.01005v12026
Exactly Computing the Local Lipschitz Constant of ReLU Networks
Matt Jordan, Alexandros G. Dimakis
stat.MLcs.LGarXiv:2003.01219v22020
Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity
Joana Lorenz, Maria Inês Silva, David Aparício +2
cs.LGstat.MLarXiv:2005.14635v22020
Removing Hidden Confounding by Experimental Grounding
Nathan Kallus, Aahlad Manas Puli, Uri Shalit
stat.MLcs.LGarXiv:1810.11646v12018
PAC-Bayesian Inequalities for Martingales
Yevgeny Seldin, François Laviolette, Nicolò Cesa-Bianchi +2
cs.LGcs.ITmath.ITarXiv:1110.6886v32011
Quantifying Differences in Reward Functions
Adam Gleave, Michael Dennis, Shane Legg +2
cs.LGcs.AIstat.MLarXiv:2006.13900v32020
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models
Emilie Kaufmann, Olivier Cappé, Aurélien Garivier
stat.MLcs.LGarXiv:1407.4443v22014
k-NN Regression Adapts to Local Intrinsic Dimension
Samory Kpotufe
stat.MLarXiv:1110.4300v12011
AudioPaLM: A Large Language Model That Can Speak and Listen
Paul K. Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen +27
cs.CLcs.AIcs.SDarXiv:2306.12925v12023
Deep Hyperspherical Learning
Weiyang Liu, Yan-Ming Zhang, Xingguo Li +4
cs.LGcs.CVstat.MLarXiv:1711.03189v52017
Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation
Dongjun Kim, Seungjae Shin, Kyungwoo Song +2
cs.LGcs.AIstat.MLarXiv:2106.05527v52021
Deep learning for time series classification: a review
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber +2
cs.LGcs.AIstat.MLarXiv:1809.04356v42018
The NetHack Learning Environment
Heinrich Küttler, Nantas Nardelli, Alexander H. Miller +4
cs.LGcs.AIcs.CLarXiv:2006.13760v22020
Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networks
Yasar Sinan Nasir, Dongning Guo
eess.SPcs.ITstat.MLarXiv:1808.00490v32018
General Cutting Planes for Bound-Propagation-Based Neural Network Verification
Huan Zhang, Shiqi Wang, Kaidi Xu +5
cs.LGcs.CRcs.CVarXiv:2208.05740v22022
CatBoost: gradient boosting with categorical features support
Anna Veronika Dorogush, Vasily Ershov, Andrey Gulin
cs.LGcs.MSstat.MLarXiv:1810.11363v12018
Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression
Sham Kakade, Adam Tauman Kalai, Varun Kanade +1
cs.AIcs.LGstat.MLarXiv:1104.2018v12011
GraphSAINT: Graph Sampling Based Inductive Learning Method
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava +2
cs.LGstat.MLarXiv:1907.04931v42019
Nonparametric semi-supervised learning of class proportions
Shantanu Jain, Martha White, Michael W. Trosset +1
stat.MLcs.LGarXiv:1601.01944v12016
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
David Salinas, Valentin Flunkert, Jan Gasthaus
cs.AIcs.LGstat.MLarXiv:1704.04110v32017
Adaptive Evolutionary Clustering
Kevin S. Xu, Mark Kliger, Alfred O. Hero III
cs.LGstat.MLarXiv:1104.1990v32011
Image Synthesis From Reconfigurable Layout and Style
Wei Sun, Tianfu Wu
cs.CVstat.MLarXiv:1908.07500v12019
Model Selection Techniques -- An Overview
Jie Ding, Vahid Tarokh, Yuhong Yang
stat.MLcs.ITcs.LGarXiv:1810.09583v12018
k-hop Graph Neural Networks
Giannis Nikolentzos, George Dasoulas, Michalis Vazirgiannis
stat.MLcs.LGarXiv:1907.06051v22019
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory
Ron Amit, Ron Meir
stat.MLcs.AIcs.LGarXiv:1711.01244v82017
Generative Poisoning Attack Method Against Neural Networks
Chaofei Yang, Qing Wu, Hai Li +1
cs.CRcs.LGstat.MLarXiv:1703.01340v12017
Guidance for Prior Change via Density Ratio Estimation
Yichen Zang, Song Liu, Jiun-Yi Lin
stat.MLcs.LGstat.MEarXiv:2608.21729v12026
Fisher GAN
Youssef Mroueh, Tom Sercu
cs.LGstat.MLarXiv:1705.09675v32017
Hyperparameter Ensembles for Robustness and Uncertainty Quantification
Florian Wenzel, Jasper Snoek, Dustin Tran +1
cs.LGstat.MLarXiv:2006.13570v32020
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
Takeru Miyato, Shin-ichi Maeda, Masanori Koyama +1
stat.MLcs.LGarXiv:1704.03976v22017
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets
Florian Tramèr, Reza Shokri, Ayrton San Joaquin +4
cs.CRcs.LGstat.MLarXiv:2204.00032v22022
ReSkill: Reconciling Skill Creation with Policy Optimization in Agentic RL
Zelin He, Haotian Lin, Boran Han +6
cs.AIcs.LGstat.MLarXiv:2606.01619v22026
Training-Adaptive Convolutional Sparse Coding via Information Bottleneck for Robust Visual Representation
Meng'en Qin, Yinchen Liu, Mingxuan Cui +1
cs.CVcs.LGstat.MLarXiv:2609.19122v22026
Inverse Problems Conditioned on Observation Ensembles: Applications and Methods
Zhengyan Huan, Camila Pazos, Martin Klassen +3
cs.LGstat.MLarXiv:2601.22029v22026
Probabilistic coherence and proper scoring rules
Joel Predd, Robert Seiringer, Elliott H. Lieb +3
stat.MLarXiv:0710.3183v12007
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
Pan Xu, Jinghui Chen, Difan Zou +1
stat.MLcs.LGmath.OCarXiv:1707.06618v32017
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy +2
cs.LGstat.MLarXiv:1906.03671v22019
Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation
Eric Zelikman, Eliana Lorch, Lester Mackey +1
cs.CLcs.AIcs.LGarXiv:2310.02304v32023
Accelerated High-Accuracy Sampling from a Warm Start via the Proximal Bouncy Particle Sampler
Fan Chen, Sinho Chewi, Jianfeng Lu +1
math.STcs.DScs.LGarXiv:2609.06905v12026
Deep Active Learning: Unified and Principled Method for Query and Training
Changjian Shui, Fan Zhou, Christian Gagné +1
cs.LGstat.MLarXiv:1911.09162v22019
When Do Neural Networks Outperform Kernel Methods?
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz +1
stat.MLcs.LGmath.STarXiv:2006.13409v22020

Machine Learning (stat)

Nonparametric ridge estimation

Finite-Sample Analysis of Proximal Gradient TD Algorithms

A Multivariate Regression Approach to Association Analysis of Quantitative Trait Network

Adversarial Objects Against LiDAR-Based Autonomous Driving Systems

An Accurate and Single-Communication Federated Inference Algorithm

Fast Two-Sample Testing with Analytic Representations of Probability Measures

Sharp Bounds on the Approximation Rates, Metric Entropy, and $n$-widths of Shallow Neural Networks

A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics

DyNet: The Dynamic Neural Network Toolkit

Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation

Random Vector Functional Link Networks for Function Approximation on Manifolds

On the Distribution of Penalized Maximum Likelihood Estimators: The LASSO, SCAD, and Thresholding

Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach

Uniform Race: Parameter-Free Approximate Rejection Sampling

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

A la Carte - Learning Fast Kernels

Distral: Robust Multitask Reinforcement Learning

Deep learning with Elastic Averaging SGD

Tolerance-Based Fairness Auditing: Violation Certification and Sensitivity Screening

Exactly Computing the Local Lipschitz Constant of ReLU Networks

Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity

Removing Hidden Confounding by Experimental Grounding

PAC-Bayesian Inequalities for Martingales

Quantifying Differences in Reward Functions

On the Complexity of Best Arm Identification in Multi-Armed Bandit Models

k-NN Regression Adapts to Local Intrinsic Dimension

AudioPaLM: A Large Language Model That Can Speak and Listen

Deep Hyperspherical Learning

Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation

Deep learning for time series classification: a review

The NetHack Learning Environment

Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networks

General Cutting Planes for Bound-Propagation-Based Neural Network Verification

CatBoost: gradient boosting with categorical features support

Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression

GraphSAINT: Graph Sampling Based Inductive Learning Method

Nonparametric semi-supervised learning of class proportions

DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

Adaptive Evolutionary Clustering

Image Synthesis From Reconfigurable Layout and Style

Model Selection Techniques -- An Overview

k-hop Graph Neural Networks

Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory

Generative Poisoning Attack Method Against Neural Networks

Guidance for Prior Change via Density Ratio Estimation

Fisher GAN

Hyperparameter Ensembles for Robustness and Uncertainty Quantification

Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning

Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets

ReSkill: Reconciling Skill Creation with Policy Optimization in Agentic RL

Training-Adaptive Convolutional Sparse Coding via Information Bottleneck for Robust Visual Representation

Inverse Problems Conditioned on Observation Ensembles: Applications and Methods

Probabilistic coherence and proper scoring rules

Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization

Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation

Accelerated High-Accuracy Sampling from a Warm Start via the Proximal Bouncy Particle Sampler

Deep Active Learning: Unified and Principled Method for Query and Training

When Do Neural Networks Outperform Kernel Methods?