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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8,641 to 8,700 of 9,674

Does Explainable Artificial Intelligence Improve Human Decision-Making?
Yasmeen Alufaisan, Laura R. Marusich, Jonathan Z. Bakdash +2
cs.LGstat.MLarXiv:2006.11194v12020
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity
Amit Daniely, Roy Frostig, Yoram Singer
cs.LGcs.AIcs.CCarXiv:1602.05897v22016
Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach
Yi Liu, Sahil Garg, Jiangtian Nie +4
cs.LGcs.DCstat.MLarXiv:2007.09712v12020
Robustness of classifiers: from adversarial to random noise
Alhussein Fawzi, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard
cs.LGcs.CVstat.MLarXiv:1608.08967v12016
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning
Michael Janner, Sergey Levine, William T. Freeman +3
cs.LGcs.AIcs.CVarXiv:1812.10972v22018
Message-passing neural networks for high-throughput polymer screening
Peter C. St. John, Caleb Phillips, Travis W. Kemper +4
physics.comp-phcs.LGstat.MLarXiv:1807.10363v22018
Low-rank Kernel Learning for Graph-based Clustering
Zhao Kang, Liangjian Wen, Wenyu Chen +1
cs.LGcs.CVstat.MLarXiv:1903.05962v12019
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks
Federico Monti, Michael M. Bronstein, Xavier Bresson
cs.LGcs.IRmath.NAarXiv:1704.06803v12017
Probabilistic Fair Clustering
Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas +1
cs.LGcs.AIcs.DSarXiv:2006.10916v32020
Unity: A General Platform for Intelligent Agents
Arthur Juliani, Vincent-Pierre Berges, Ervin Teng +8
cs.LGcs.AIcs.NEarXiv:1809.02627v22018
Encoder Based Lifelong Learning
Amal Rannen Triki, Rahaf Aljundi, Mathew B. Blaschko +1
cs.CVcs.AIstat.MLarXiv:1704.01920v12017
Learning Invariant Representations for Reinforcement Learning without Reconstruction
Amy Zhang, Rowan McAllister, Roberto Calandra +2
cs.LGcs.AIstat.MLarXiv:2006.10742v22020
Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems
Mohsen Shahhosseini, Guiping Hu, Hieu Pham
stat.MLcs.LGstat.MEarXiv:1908.05287v62019
DFacTo: Distributed Factorization of Tensors
Joon Hee Choi, S. V. N. Vishwanathan
stat.MLarXiv:1406.4519v12014
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Oran Lang, Yossi Gandelsman, Michal Yarom +8
cs.CVcs.LGcs.NEarXiv:2104.13369v22021
Controlling false discoveries in high-dimensional situations: Boosting with stability selection
Benjamin Hofner, Luigi Boccuto, Markus Göker
stat.MLstat.APstat.COarXiv:1411.1285v12014
In-Place Test-Time Training
Guhao Feng, Shengjie Luo, Kai Hua +4
cs.LGcs.AIcs.CLarXiv:2604.06169v12026
MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot, Nicholas Carlini, Ian Goodfellow +3
cs.LGcs.AIcs.CVarXiv:1905.02249v22019
Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence
Nicolas Donati, Abhishek Sharma, Maks Ovsjanikov
stat.MLcs.LGarXiv:2003.14286v12020
Learning Nonlinear Functions Using Regularized Greedy Forest
Rie Johnson, Tong Zhang
stat.MLarXiv:1109.0887v72011
Adaptive Federated Optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer +5
cs.LGcs.DCmath.OCarXiv:2003.00295v52020
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
Tzu-Ming Harry Hsu, Hang Qi, Matthew Brown
cs.LGcs.CVstat.MLarXiv:1909.06335v12019
Towards Deeper Graph Neural Networks
Meng Liu, Hongyang Gao, Shuiwang Ji
cs.LGstat.MLarXiv:2007.09296v12020
Simple And Efficient Architecture Search for Convolutional Neural Networks
Thomas Elsken, Jan-Hendrik Metzen, Frank Hutter
stat.MLcs.AIcs.LGarXiv:1711.04528v12017
A Literature Study of Embeddings on Source Code
Zimin Chen, Martin Monperrus
cs.LGcs.PLcs.SEarXiv:1904.03061v12019
PAC-Bayesian Theory Meets Bayesian Inference
Pascal Germain, Francis Bach, Alexandre Lacoste +1
stat.MLcs.LGarXiv:1605.08636v42016
Learning Combinatorial Optimization on Graphs: A Survey with Applications to Networking
Natalia Vesselinova, Rebecca Steinert, Daniel F. Perez-Ramirez +1
cs.LGcs.AIstat.MLarXiv:2005.11081v22020
The Bayesian Learning Rule
Mohammad Emtiyaz Khan, Håvard Rue
stat.MLcs.LGarXiv:2107.04562v42021
What Algorithms can Transformers Learn? A Study in Length Generalization
Hattie Zhou, Arwen Bradley, Etai Littwin +5
cs.LGcs.AIcs.CLarXiv:2310.16028v12023
Stochastic Gradient Hamiltonian Monte Carlo
Tianqi Chen, Emily B. Fox, Carlos Guestrin
stat.MEcs.LGstat.MLarXiv:1402.4102v22014
Causal DAG Identification for Count Data via Poisson Thinning Structural Equation Models
Penggang Gao, Ming Cai, Hisayuki Hara
stat.MEcs.LGstat.MLarXiv:2609.06098v12026
Convolutional Kernel Networks
Julien Mairal, Piotr Koniusz, Zaid Harchaoui +1
cs.CVcs.LGstat.MLarXiv:1406.3332v22014
Unexpected Improvements to Expected Improvement for Bayesian Optimization
Sebastian Ament, Samuel Daulton, David Eriksson +2
cs.LGmath.NAstat.MLarXiv:2310.20708v32023
Summaries:한국어
Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares
Trevor Hastie, Rahul Mazumder, Jason Lee +1
stat.MEstat.MLarXiv:1410.2596v12014
Gauss--Hermite Quadrature for Gaussian-Mixture Entropy with an Action-Space Hermite Surrogate
Jae Wan Shim
stat.MLcs.ITcs.LGarXiv:2608.21467v22026
Enhancing Generative Models via Quantum Correlations
Xun Gao, Eric R. Anschuetz, Sheng-Tao Wang +2
quant-phcond-mat.stat-mechcs.LGarXiv:2101.08354v12021
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds
Xiaohan Chen, Jialin Liu, Zhangyang Wang +1
cs.LGstat.MLarXiv:1808.10038v22018
Reinforcement Learning with Verifiable Rewards: GRPO's Effective Loss, Dynamics, and Success Amplification
Youssef Mroueh
cs.LGstat.MLarXiv:2503.06639v42025
VA-learning as a more efficient alternative to Q-learning
Yunhao Tang, Rémi Munos, Mark Rowland +1
cs.LGstat.MLarXiv:2305.18161v22023
Spherical CNNs
Taco S. Cohen, Mario Geiger, Jonas Koehler +1
cs.LGstat.MLarXiv:1801.10130v32018
Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming
Itay Hubara, Yury Nahshan, Yair Hanani +2
cs.LGstat.MLarXiv:2006.10518v22020
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings
Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo +14
cs.LGcs.CYstat.MLarXiv:2202.01034v22022
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang, Tiffany Tuor, Theodoros Salonidis +4
cs.DCcs.LGmath.OCarXiv:1804.05271v32018
Provably Consistent Partial-Label Learning
Lei Feng, Jiaqi Lv, Bo Han +5
cs.LGstat.MLarXiv:2007.08929v22020
From optimal transport to generative modeling: the VEGAN cookbook
Olivier Bousquet, Sylvain Gelly, Ilya Tolstikhin +2
stat.MLarXiv:1705.07642v12017
Theoretical Benefit and Limitation of Diffusion Language Model
Guhao Feng, Yihan Geng, Jian Guan +3
cs.LGcs.AIcs.CLarXiv:2502.09622v22025
Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations: Column Combining Under Joint Optimization
H. T. Kung, Bradley McDanel, Sai Qian Zhang
cs.LGcs.ARstat.MLarXiv:1811.04770v12018
Batch Bayesian Optimization via Local Penalization
Javier González, Zhenwen Dai, Philipp Hennig +1
stat.MLarXiv:1505.08052v42015
Train faster, generalize better: Stability of stochastic gradient descent
Moritz Hardt, Benjamin Recht, Yoram Singer
cs.LGmath.OCstat.MLarXiv:1509.01240v22015
The Nonparanormal SKEPTIC
Han Liu, Fang Han, Ming Yuan +2
stat.MEcs.LGstat.MLarXiv:1206.6488v12012
Deep Sufficient Representation Learning via Mutual Information
Siming Zheng, Yuanyuan Lin, Jian Huang
stat.MLcs.LGarXiv:2207.10772v12022
Distributed learning of deep neural network over multiple agents
Otkrist Gupta, Ramesh Raskar
cs.LGstat.MLarXiv:1810.06060v12018
Improving Certified Robustness via Statistical Learning with Logical Reasoning
Zhuolin Yang, Zhikuan Zhao, Boxin Wang +8
cs.LGcs.CRstat.MLarXiv:2003.00120v92020
Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning
Felix Leibfried, Jordi Grau-Moya
cs.LGcs.AIstat.MLarXiv:1909.05950v12019
An optimal algorithm for the Thresholding Bandit Problem
Andrea Locatelli, Maurilio Gutzeit, Alexandra Carpentier
stat.MLcs.LGarXiv:1605.08671v12016
From Log-Odds to Shapley Values: An Explanatory Geometry for the Weighted Naive Bayes Classifier
Vincent Lemaire, Fabrice Clérot
stat.MLcs.AIcs.LGarXiv:2610.10642v12026
Kernel density estimation based sampling for imbalanced class distribution
Firuz Kamalov
cs.LGstat.MLarXiv:1910.07842v22019
Practical Gauss-Newton Optimisation for Deep Learning
Aleksandar Botev, Hippolyt Ritter, David Barber
stat.MLarXiv:1706.03662v22017
A Concise Review of Recent Few-shot Meta-learning Methods
Xiaoxu Li, Zhuo Sun, Jing-Hao Xue +1
cs.LGcs.CVstat.MLarXiv:2005.10953v12020
The Recurrent Neural Tangent Kernel
Sina Alemohammad, Zichao Wang, Randall Balestriero +1
cs.LGstat.MLarXiv:2006.10246v42020

Machine Learning (stat)

Does Explainable Artificial Intelligence Improve Human Decision-Making?

Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity

Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

Robustness of classifiers: from adversarial to random noise

Reasoning About Physical Interactions with Object-Oriented Prediction and Planning

Message-passing neural networks for high-throughput polymer screening

Low-rank Kernel Learning for Graph-based Clustering

Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks

Probabilistic Fair Clustering

Unity: A General Platform for Intelligent Agents

Encoder Based Lifelong Learning

Learning Invariant Representations for Reinforcement Learning without Reconstruction

Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems

DFacTo: Distributed Factorization of Tensors

Explaining in Style: Training a GAN to explain a classifier in StyleSpace

Controlling false discoveries in high-dimensional situations: Boosting with stability selection

In-Place Test-Time Training

MixMatch: A Holistic Approach to Semi-Supervised Learning

Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence

Learning Nonlinear Functions Using Regularized Greedy Forest

Adaptive Federated Optimization

Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Towards Deeper Graph Neural Networks

Simple And Efficient Architecture Search for Convolutional Neural Networks

A Literature Study of Embeddings on Source Code

PAC-Bayesian Theory Meets Bayesian Inference

Learning Combinatorial Optimization on Graphs: A Survey with Applications to Networking

The Bayesian Learning Rule

What Algorithms can Transformers Learn? A Study in Length Generalization

Stochastic Gradient Hamiltonian Monte Carlo

Causal DAG Identification for Count Data via Poisson Thinning Structural Equation Models

Convolutional Kernel Networks

Unexpected Improvements to Expected Improvement for Bayesian Optimization

Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares

Gauss--Hermite Quadrature for Gaussian-Mixture Entropy with an Action-Space Hermite Surrogate

Enhancing Generative Models via Quantum Correlations

Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds

Reinforcement Learning with Verifiable Rewards: GRPO's Effective Loss, Dynamics, and Success Amplification

VA-learning as a more efficient alternative to Q-learning

Spherical CNNs

Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming

Diagnosing failures of fairness transfer across distribution shift in real-world medical settings

Adaptive Federated Learning in Resource Constrained Edge Computing Systems

Provably Consistent Partial-Label Learning

From optimal transport to generative modeling: the VEGAN cookbook

Theoretical Benefit and Limitation of Diffusion Language Model

Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations: Column Combining Under Joint Optimization

Batch Bayesian Optimization via Local Penalization

Train faster, generalize better: Stability of stochastic gradient descent

The Nonparanormal SKEPTIC

Deep Sufficient Representation Learning via Mutual Information

Distributed learning of deep neural network over multiple agents

Improving Certified Robustness via Statistical Learning with Logical Reasoning

Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning

An optimal algorithm for the Thresholding Bandit Problem

From Log-Odds to Shapley Values: An Explanatory Geometry for the Weighted Naive Bayes Classifier

Kernel density estimation based sampling for imbalanced class distribution

Practical Gauss-Newton Optimisation for Deep Learning

A Concise Review of Recent Few-shot Meta-learning Methods

The Recurrent Neural Tangent Kernel