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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1,441 to 1,500 of 6,790

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
Jiezhong Qiu, Yuxiao Dong, Hao Ma +4
cs.SIcs.LGstat.MLarXiv:1906.11156v12019
Learning the Structure of Generative Models without Labeled Data
Stephen H. Bach, Bryan He, Alexander Ratner +1
cs.LGstat.MLarXiv:1703.00854v22017
Estimating Time-varying Brain Connectivity Networks from Functional MRI Time Series
Ricardo Pio Monti, Peter Hellyer, David Sharp +3
stat.MLstat.AParXiv:1310.3863v22013
Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees
Daniil Dmitriev, Zhihan Huang, Yuting Wei
cs.LGcs.ITmath.STarXiv:2602.15008v22026
Imitating Latent Policies from Observation
Ashley D. Edwards, Himanshu Sahni, Yannick Schroecker +1
cs.LGstat.MLarXiv:1805.07914v32018
Sharp convergence rates for Langevin dynamics in the nonconvex setting
Xiang Cheng, Niladri S. Chatterji, Yasin Abbasi-Yadkori +2
stat.MLcs.LGmath.PRarXiv:1805.01648v42018
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Yuzhe Yang, Guo Zhang, Dina Katabi +1
cs.LGcs.CVstat.MLarXiv:1905.11971v12019
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search
Arthur Guez, David Silver, Peter Dayan
cs.LGcs.AIstat.MLarXiv:1205.3109v42012
A Variational Analysis of Stochastic Gradient Algorithms
Stephan Mandt, Matthew D. Hoffman, David M. Blei
stat.MLcs.LGarXiv:1602.02666v12016
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case
Greg Ongie, Rebecca Willett, Daniel Soudry +1
cs.LGstat.MLarXiv:1910.01635v12019
Kernels for sequentially ordered data
Franz J Király, Harald Oberhauser
stat.MLcs.DMcs.LGarXiv:1601.08169v12016
Adaptive Algorithms for Online Convex Optimization with Long-term Constraints
Rodolphe Jenatton, Jim Huang, Cédric Archambeau
stat.MLcs.LGmath.OCarXiv:1512.07422v12015
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning
Talip Ucar, Ehsan Hajiramezanali, Lindsay Edwards
cs.LGstat.MLarXiv:2110.04361v22021
Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling
Zeyuan Allen-Zhu, Zheng Qu, Peter Richtárik +1
math.OCcs.DSmath.NAarXiv:1512.09103v32015
Artificial Intelligence and Statistics
Bin Yu, Karl Kumbier
stat.MLcs.AIarXiv:1712.03779v12017
Certifiable Robustness and Robust Training for Graph Convolutional Networks
Daniel Zügner, Stephan Günnemann
cs.LGcs.CRstat.MLarXiv:1906.12269v12019
RayS: A Ray Searching Method for Hard-label Adversarial Attack
Jinghui Chen, Quanquan Gu
cs.LGcs.AIstat.MLarXiv:2006.12792v22020
Dropping Convexity for Faster Semi-definite Optimization
Srinadh Bhojanapalli, Anastasios Kyrillidis, Sujay Sanghavi
stat.MLcs.DScs.ITarXiv:1509.03917v32015
Characterizing Audio Adversarial Examples Using Temporal Dependency
Zhuolin Yang, Bo Li, Pin-Yu Chen +1
cs.LGcs.AIcs.CRarXiv:1809.10875v22018
Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments
Rémy Portelas, Cédric Colas, Katja Hofmann +1
cs.LGcs.ROstat.MLarXiv:1910.07224v12019
Learning Nearly Decomposable Value Functions Via Communication Minimization
Tonghan Wang, Jianhao Wang, Chongyi Zheng +1
cs.LGstat.MLarXiv:1910.05366v22019
Task-Aware Variational Adversarial Active Learning
Kwanyoung Kim, Dongwon Park, Kwang In Kim +1
cs.LGstat.MLarXiv:2002.04709v22020
Almost Optimal Model-Free Reinforcement Learning via Reference-Advantage Decomposition
Zihan Zhang, Yuan Zhou, Xiangyang Ji
cs.LGcs.DSstat.MLarXiv:2004.10019v22020
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models
Litu Rout, Negin Raoof, Giannis Daras +3
cs.LGcs.AIstat.MLarXiv:2307.00619v12023
An Overview of Melanoma Detection in Dermoscopy Images Using Image Processing and Machine Learning
Nabin K. Mishra, M. Emre Celebi
cs.CVstat.MLarXiv:1601.07843v12016
Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data
Jorge Samper-González, Ninon Burgos, Simona Bottani +13
cs.LGstat.MLarXiv:1808.06452v12018
The Information Bottleneck Problem and Its Applications in Machine Learning
Ziv Goldfeld, Yury Polyanskiy
cs.LGstat.MLarXiv:2004.14941v22020
Similarity-based Android Malware Detection Using Hamming Distance of Static Binary Features
Rahim Taheri, Meysam Ghahramani, Reza Javidan +3
cs.CRcs.LGcs.NEarXiv:1908.05759v22019
Distillation Scaling Laws
Dan Busbridge, Amitis Shidani, Floris Weers +3
cs.LGcs.AIcs.CLarXiv:2502.08606v22025
Structured Disentangled Representations
Babak Esmaeili, Hao Wu, Sarthak Jain +6
stat.MLcs.LGarXiv:1804.02086v42018
Sliced Wasserstein Kernels for Probability Distributions
Soheil Kolouri, Yang Zou, Gustavo K. Rohde
cs.LGstat.MLarXiv:1511.03198v12015
A convolutional framework for detecting event-driven dynamics in energy price series
Caixia Xu, Piotr Fryzlewicz
stat.MLcs.LGstat.MEarXiv:2609.00402v12026
Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes
Carlo Baldassi, Christian Borgs, Jennifer Chayes +4
stat.MLcond-mat.dis-nncs.LGarXiv:1605.06444v32016
Free-rider Attacks on Model Aggregation in Federated Learning
Yann Fraboni, Richard Vidal, Marco Lorenzi
cs.LGstat.MLarXiv:2006.11901v52020
Fast Task Inference with Variational Intrinsic Successor Features
Steven Hansen, Will Dabney, Andre Barreto +3
cs.LGcs.AIstat.MLarXiv:1906.05030v22019
Scalable detection of statistically significant communities and hierarchies, using message-passing for modularity
Pan Zhang, Cristopher Moore
physics.soc-phcond-mat.stat-mechcs.SIarXiv:1403.5787v32014
Multi-level Residual Networks from Dynamical Systems View
Bo Chang, Lili Meng, Eldad Haber +2
stat.MLcs.CVarXiv:1710.10348v22017
Extremely Fast Decision Tree
Chaitanya Manapragada, Geoff Webb, Mahsa Salehi
cs.LGstat.MLarXiv:1802.08780v12018
Wasserstein Learning of Deep Generative Point Process Models
Shuai Xiao, Mehrdad Farajtabar, Xiaojing Ye +3
cs.LGstat.MLarXiv:1705.08051v12017
Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization
Minsu Kim, Junyoung Park, Jinkyoo Park
cs.LGstat.MLarXiv:2205.13209v22022
Provable Inductive Matrix Completion
Prateek Jain, Inderjit S. Dhillon
cs.LGcs.ITstat.MLarXiv:1306.0626v12013
Hashing with binary autoencoders
Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei
cs.LGcs.CVmath.OCarXiv:1501.00756v12015
NAS evaluation is frustratingly hard
Antoine Yang, Pedro M. Esperança, Fabio M. Carlucci
cs.LGcs.CVstat.MLarXiv:1912.12522v32019
Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream
Amr Ahmed, Eric P. Xing
cs.IRcs.LGstat.MLarXiv:1203.3463v12012
Solving Linear Inverse Problems Using GAN Priors: An Algorithm with Provable Guarantees
Viraj Shah, Chinmay Hegde
stat.MLcs.LGarXiv:1802.08406v12018
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling
Jianyu Wang, Anit Kumar Sahu, Zhouyi Yang +2
cs.LGeess.SYmath.OCarXiv:1905.09435v32019
Score-Based Causal Discovery of Latent Variable Causal Models
Ignavier Ng, Xinshuai Dong, Haoyue Dai +3
cs.LGstat.MLarXiv:2605.20396v12026
The Optimal Sample Complexity of PAC Learning
Steve Hanneke
cs.LGstat.MLarXiv:1507.00473v42015
Implicit Graph Neural Networks
Fangda Gu, Heng Chang, Wenwu Zhu +2
cs.LGstat.MLarXiv:2009.06211v32020
Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention
Ming Zeng, Haoxiang Gao, Tong Yu +4
cs.LGcs.AIstat.MLarXiv:1810.04038v12018
CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin Liang, Guanghui Lan
cs.LGstat.MLarXiv:2011.05869v32020
Deep Learning for Reliable Mobile Edge Analytics in Intelligent Transportation Systems
Aidin Ferdowsi, Ursula Challita, Walid Saad
cs.ITstat.MLarXiv:1712.04135v12017
Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications
Jihong Park, Sumudu Samarakoon, Anis Elgabli +4
cs.LGcs.ITcs.NIarXiv:2008.02608v12020
End-to-End Deep Reinforcement Learning for Lane Keeping Assist
Ahmad El Sallab, Mohammed Abdou, Etienne Perot +1
stat.MLcs.LGcs.ROarXiv:1612.04340v12016
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
Deep Learning and Its Applications to Machine Health Monitoring: A Survey
Rui Zhao, Ruqiang Yan, Zhenghua Chen +3
cs.LGstat.MLarXiv:1612.07640v12016
Recent Advances in Zero-shot Recognition
Yanwei Fu, Tao Xiang, Yu-Gang Jiang +3
cs.CVcs.AIcs.LGarXiv:1710.04837v12017
Optimization for deep learning: theory and algorithms
Ruoyu Sun
cs.LGmath.OCstat.MLarXiv:1912.08957v12019
Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research
Bernard Koch, Emily Denton, Alex Hanna +1
cs.LGcs.CLcs.CVarXiv:2112.01716v12021
Parallel Bayesian Global Optimization of Expensive Functions
Jialei Wang, Scott C. Clark, Eric Liu +1
stat.MLmath.OCarXiv:1602.05149v42016

Machine Learning (stat)

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

Learning the Structure of Generative Models without Labeled Data

Estimating Time-varying Brain Connectivity Networks from Functional MRI Time Series

Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees

Imitating Latent Policies from Observation

Sharp convergence rates for Langevin dynamics in the nonconvex setting

ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search

A Variational Analysis of Stochastic Gradient Algorithms

A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case

Kernels for sequentially ordered data

Adaptive Algorithms for Online Convex Optimization with Long-term Constraints

SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning

Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling

Artificial Intelligence and Statistics

Certifiable Robustness and Robust Training for Graph Convolutional Networks

RayS: A Ray Searching Method for Hard-label Adversarial Attack

Dropping Convexity for Faster Semi-definite Optimization

Characterizing Audio Adversarial Examples Using Temporal Dependency

Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments

Learning Nearly Decomposable Value Functions Via Communication Minimization

Task-Aware Variational Adversarial Active Learning

Almost Optimal Model-Free Reinforcement Learning via Reference-Advantage Decomposition

Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models

An Overview of Melanoma Detection in Dermoscopy Images Using Image Processing and Machine Learning

Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data

The Information Bottleneck Problem and Its Applications in Machine Learning

Similarity-based Android Malware Detection Using Hamming Distance of Static Binary Features

Distillation Scaling Laws

Structured Disentangled Representations

Sliced Wasserstein Kernels for Probability Distributions

A convolutional framework for detecting event-driven dynamics in energy price series

Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes

Free-rider Attacks on Model Aggregation in Federated Learning

Fast Task Inference with Variational Intrinsic Successor Features

Scalable detection of statistically significant communities and hierarchies, using message-passing for modularity

Multi-level Residual Networks from Dynamical Systems View

Extremely Fast Decision Tree

Wasserstein Learning of Deep Generative Point Process Models

Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization

Provable Inductive Matrix Completion

Hashing with binary autoencoders

NAS evaluation is frustratingly hard

Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream

Solving Linear Inverse Problems Using GAN Priors: An Algorithm with Provable Guarantees

MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling

Score-Based Causal Discovery of Latent Variable Causal Models

The Optimal Sample Complexity of PAC Learning

Implicit Graph Neural Networks

Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention

CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee

Deep Learning for Reliable Mobile Edge Analytics in Intelligent Transportation Systems

Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications

End-to-End Deep Reinforcement Learning for Lane Keeping Assist

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

Deep Learning and Its Applications to Machine Health Monitoring: A Survey

Recent Advances in Zero-shot Recognition

Optimization for deep learning: theory and algorithms

Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research

Parallel Bayesian Global Optimization of Expensive Functions