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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2,461 to 2,520 of 6,790

Optimal detection of sparse principal components in high dimension
Quentin Berthet, Philippe Rigollet
math.STstat.MLarXiv:1202.5070v32012
Convergence of latent mixing measures in finite and infinite mixture models
XuanLong Nguyen
math.STstat.MLarXiv:1109.3250v52011
Spectral Methods for Learning Multivariate Latent Tree Structure
Animashree Anandkumar, Kamalika Chaudhuri, Daniel Hsu +3
cs.LGstat.MLarXiv:1107.1283v22011
Distributed Delayed Stochastic Optimization
Alekh Agarwal, John C. Duchi
math.OCstat.MLarXiv:1104.5525v12011
Sparse Signal Recovery with Temporally Correlated Source Vectors Using Sparse Bayesian Learning
Zhilin Zhang, Bhaskar D. Rao
stat.MLcs.LGarXiv:1102.3949v22011
Robust PCA via Outlier Pursuit
Huan Xu, Constantine Caramanis, Sujay Sanghavi
cs.LGcs.ITstat.MLarXiv:1010.4237v22010
A survey of statistical network models
Anna Goldenberg, Alice X Zheng, Stephen E Fienberg +1
stat.MEcs.LGphysics.soc-pharXiv:0912.5410v12009
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger +5
stat.MLcs.AIcs.LGarXiv:1903.06694v22019
MisGAN: Learning from Incomplete Data with Generative Adversarial Networks
Steven Cheng-Xian Li, Bo Jiang, Benjamin Marlin
cs.LGstat.MLarXiv:1902.09599v12019
When Metropolis and Hastings Meet Bradley and Terry: Exact MCMC From Preference Voting
Ariel Smogorghevski, Nir Rosenfeld, Yaniv Romano
cs.LGstat.COstat.MLarXiv:2609.00905v12026
Chronos-2: From Univariate to Universal Forecasting
Abdul Fatir Ansari, Oleksandr Shchur, Jaris Küken +20
cs.LGcs.AIstat.MLarXiv:2510.15821v12025
What Can ResNet Learn Efficiently, Going Beyond Kernels?
Zeyuan Allen-Zhu, Yuanzhi Li
cs.LGcs.DScs.NEarXiv:1905.10337v32019
Loss minimization and parameter estimation with heavy tails
Daniel Hsu, Sivan Sabato
cs.LGstat.MLarXiv:1307.1827v72013
Deep Neural Network Compression for Aircraft Collision Avoidance Systems
Kyle D. Julian, Mykel J. Kochenderfer, Michael P. Owen
cs.LGstat.MLarXiv:1810.04240v12018
Meta-Learning without Memorization
Mingzhang Yin, George Tucker, Mingyuan Zhou +2
cs.LGcs.AIstat.MLarXiv:1912.03820v32019
On Feature Learning in the Presence of Spurious Correlations
Pavel Izmailov, Polina Kirichenko, Nate Gruver +1
cs.LGcs.CVstat.MLarXiv:2210.11369v12022
Improved Gradient Descent Lower Bounds Beyond Nesterov
Yuhan Ye, Kaizhao Liu
math.OCcs.LGstat.MLarXiv:2609.02855v22026
A ROAD to Classification in High Dimensional Space
Jianqing Fan, Yang Feng, Xin Tong
stat.MLstat.MEarXiv:1011.6095v22010
Automated Directed Fairness Testing
Sakshi Udeshi, Pryanshu Arora, Sudipta Chattopadhyay
cs.LGcs.AIcs.SEarXiv:1807.00468v22018
Cascaded V-Net using ROI masks for brain tumor segmentation
Adrià Casamitjana, Marcel Catà, Irina Sánchez +2
cs.CVcs.AIcs.CYarXiv:1812.11588v12018
Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization
Izhar Wallach, Abraham Heifets
q-bio.QMcs.LGstat.MLarXiv:1706.06619v22017
Survey of state-of-the-art mixed data clustering algorithms
Amir Ahmad, Shehroz S. Khan
cs.LGcs.AIstat.MLarXiv:1811.04364v62018
Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities
Dong Huang, Chang-Dong Wang, Hongxing Peng +2
cs.LGstat.MLarXiv:1810.12544v12018
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
Randall Balestriero, Yann LeCun
cs.LGcs.AIcs.CVarXiv:2511.08544v32025
Learning Mixtures of Submodular Shells with Application to Document Summarization
Hui Lin, Jeff A. Bilmes
cs.LGcs.CLcs.IRarXiv:1210.4871v12012
Fast and Eager k-Medoids Clustering: O(k) Runtime Improvement of the PAM, CLARA, and CLARANS Algorithms
Erich Schubert, Peter J. Rousseeuw
cs.LGcs.AIstat.MLarXiv:2008.05171v22020
Tree-based Intelligent Intrusion Detection System in Internet of Vehicles
Li Yang, Abdallah Moubayed, Ismail Hamieh +1
cs.LGcs.CRstat.MLarXiv:1910.08635v22019
Practical Deep Reinforcement Learning Approach for Stock Trading
Xiao-Yang Liu, Zhuoran Xiong, Shan Zhong +2
cs.LGq-fin.TRstat.MLarXiv:1811.07522v32018
Momentum in large-batch training: Polyak enlarges the critical batch size, Nesterov improves data efficiency
Jia-Nan Wang, Zixun Huang, Kairui Li +1
stat.MLcs.LGmath.OCarXiv:2609.02728v12026
A Unified Approach to Error Bounds for Structured Convex Optimization Problems
Zirui Zhou, Anthony Man-Cho So
math.OCcs.LGmath.NAarXiv:1512.03518v12015
Deep Probabilistic Programming
Dustin Tran, Matthew D. Hoffman, Rif A. Saurous +3
stat.MLcs.AIcs.LGarXiv:1701.03757v22017
Differentiable plasticity: training plastic neural networks with backpropagation
Thomas Miconi, Jeff Clune, Kenneth O. Stanley
cs.NEcs.LGstat.MLarXiv:1804.02464v32018
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?
Samet Oymak, Mahdi Soltanolkotabi
cs.LGmath.OCstat.MLarXiv:1812.10004v12018
Machine-Learning-Based Diagnostics of EEG Pathology
Lukas Alexander Wilhelm Gemein, Robin Tibor Schirrmeister, Patryk Chrabąszcz +5
eess.IVcs.LGeess.SParXiv:2002.05115v12020
Molecule Attention Transformer
Łukasz Maziarka, Tomasz Danel, Sławomir Mucha +3
cs.LGphysics.comp-phstat.MLarXiv:2002.08264v12020
Inferring deterministic causal relations
Povilas Daniusis, Dominik Janzing, Joris Mooij +4
cs.LGstat.MLarXiv:1203.3475v12012
MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation
Sanjay Kariyappa, Atul Prakash, Moinuddin Qureshi
stat.MLcs.LGarXiv:2005.03161v22020
Trace Lasso: a trace norm regularization for correlated designs
Edouard Grave, Guillaume Obozinski, Francis Bach
cs.LGstat.MLarXiv:1109.1990v12011
RAB: Provable Robustness Against Backdoor Attacks
Maurice Weber, Xiaojun Xu, Bojan Karlaš +2
cs.LGstat.MLarXiv:2003.08904v82020
Summaries:한국어
Distributed Matrix Completion and Robust Factorization
Lester Mackey, Ameet Talwalkar, Michael I. Jordan
cs.LGcs.DSmath.NAarXiv:1107.0789v72011
Learning from Distributions via Support Measure Machines
Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo +1
stat.MLcs.LGarXiv:1202.6504v22012
Nonparametric Bayesian inference of the microcanonical stochastic block model
Tiago P. Peixoto
physics.data-anphysics.soc-phstat.MLarXiv:1610.02703v42016
Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?
Nitin Bansal, Xiaohan Chen, Zhangyang Wang
cs.LGcs.CVstat.MLarXiv:1810.09102v12018
Strong oracle optimality of folded concave penalized estimation
Jianqing Fan, Lingzhou Xue, Hui Zou
math.STstat.COstat.MLarXiv:1210.5992v42012
Gradient Coding from Cyclic MDS Codes and Expander Graphs
Netanel Raviv, Itzhak Tamo, Rashish Tandon +1
cs.ITstat.MLarXiv:1707.03858v32017
Targeted Adversarial Examples for Black Box Audio Systems
Rohan Taori, Amog Kamsetty, Brenton Chu +1
cs.LGcs.CRcs.SDarXiv:1805.07820v22018
FastSHAP: Real-Time Shapley Value Estimation
Neil Jethani, Mukund Sudarshan, Ian Covert +2
stat.MLcs.CVcs.LGarXiv:2107.07436v32021
Multi-class Classification without Multi-class Labels
Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser +2
cs.LGcs.AIcs.CVarXiv:1901.00544v12019
Sure independence screening in generalized linear models with NP-dimensionality
Jianqing Fan, Rui Song
stat.MEmath.STstat.MLarXiv:0903.5255v52009
Graph Meta Learning via Local Subgraphs
Kexin Huang, Marinka Zitnik
cs.LGstat.MLarXiv:2006.07889v42020
Causal Bandits: Learning Good Interventions via Causal Inference
Finnian Lattimore, Tor Lattimore, Mark D. Reid
stat.MLcs.LGarXiv:1606.03203v12016
Support union recovery in high-dimensional multivariate regression
Guillaume Obozinski, Martin J. Wainwright, Michael I. Jordan
stat.MLmath.STarXiv:0808.0711v22008
Leveraging Big Data Analytics in Healthcare Enhancement: Trends, Challenges and Opportunities
Arshia Rehman, Saeeda Naz, Imran Razzak
stat.OTcs.LGstat.MLarXiv:2004.09010v12020
Fast rates for support vector machines using Gaussian kernels
Ingo Steinwart, Clint Scovel
math.STstat.MLarXiv:0708.1838v12007
Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon
Yoshua Bengio, Andrea Lodi, Antoine Prouvost
cs.LGstat.MLarXiv:1811.06128v22018
Emergence of Invariance and Disentanglement in Deep Representations
Alessandro Achille, Stefano Soatto
cs.LGcs.AIstat.MLarXiv:1706.01350v32017
Spectral clustering and the high-dimensional stochastic blockmodel
Karl Rohe, Sourav Chatterjee, Bin Yu
stat.MLmath.STarXiv:1007.1684v32010
BART: Bayesian additive regression trees
Hugh A. Chipman, Edward I. George, Robert E. McCulloch
stat.MEstat.APstat.MLarXiv:0806.3286v22008
A Systematic Survey on Deep Generative Models for Graph Generation
Xiaojie Guo, Liang Zhao
cs.LGstat.MLarXiv:2007.06686v32020
F*: An Interpretable Transformation of the F-measure
David J. Hand, Peter Christen, Nishadi Kirielle
cs.LGcs.AIcs.CVarXiv:2008.00103v32020

Machine Learning (stat)

Optimal detection of sparse principal components in high dimension

Convergence of latent mixing measures in finite and infinite mixture models

Spectral Methods for Learning Multivariate Latent Tree Structure

Distributed Delayed Stochastic Optimization

Sparse Signal Recovery with Temporally Correlated Source Vectors Using Sparse Bayesian Learning

Robust PCA via Outlier Pursuit

A survey of statistical network models

Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly

MisGAN: Learning from Incomplete Data with Generative Adversarial Networks

When Metropolis and Hastings Meet Bradley and Terry: Exact MCMC From Preference Voting

Chronos-2: From Univariate to Universal Forecasting

What Can ResNet Learn Efficiently, Going Beyond Kernels?

Loss minimization and parameter estimation with heavy tails

Deep Neural Network Compression for Aircraft Collision Avoidance Systems

Meta-Learning without Memorization

On Feature Learning in the Presence of Spurious Correlations

Improved Gradient Descent Lower Bounds Beyond Nesterov

A ROAD to Classification in High Dimensional Space

Automated Directed Fairness Testing

Cascaded V-Net using ROI masks for brain tumor segmentation

Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization

Survey of state-of-the-art mixed data clustering algorithms

Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities

LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics

Learning Mixtures of Submodular Shells with Application to Document Summarization

Fast and Eager k-Medoids Clustering: O(k) Runtime Improvement of the PAM, CLARA, and CLARANS Algorithms

Tree-based Intelligent Intrusion Detection System in Internet of Vehicles

Practical Deep Reinforcement Learning Approach for Stock Trading

Momentum in large-batch training: Polyak enlarges the critical batch size, Nesterov improves data efficiency

A Unified Approach to Error Bounds for Structured Convex Optimization Problems

Deep Probabilistic Programming

Differentiable plasticity: training plastic neural networks with backpropagation

Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?

Machine-Learning-Based Diagnostics of EEG Pathology

Molecule Attention Transformer

Inferring deterministic causal relations

MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation

Trace Lasso: a trace norm regularization for correlated designs

RAB: Provable Robustness Against Backdoor Attacks

Distributed Matrix Completion and Robust Factorization

Learning from Distributions via Support Measure Machines

Nonparametric Bayesian inference of the microcanonical stochastic block model

Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?

Strong oracle optimality of folded concave penalized estimation

Gradient Coding from Cyclic MDS Codes and Expander Graphs

Targeted Adversarial Examples for Black Box Audio Systems

FastSHAP: Real-Time Shapley Value Estimation

Multi-class Classification without Multi-class Labels

Sure independence screening in generalized linear models with NP-dimensionality

Graph Meta Learning via Local Subgraphs

Causal Bandits: Learning Good Interventions via Causal Inference

Support union recovery in high-dimensional multivariate regression

Leveraging Big Data Analytics in Healthcare Enhancement: Trends, Challenges and Opportunities

Fast rates for support vector machines using Gaussian kernels

Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon

Emergence of Invariance and Disentanglement in Deep Representations

Spectral clustering and the high-dimensional stochastic blockmodel

BART: Bayesian additive regression trees

A Systematic Survey on Deep Generative Models for Graph Generation

F*: An Interpretable Transformation of the F-measure