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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3,901 to 3,960 of 6,792

Self-Distillation Amplifies Regularization in Hilbert Space
Hossein Mobahi, Mehrdad Farajtabar, Peter L. Bartlett
cs.LGstat.MLarXiv:2002.05715v32020
Learning Stochastic Recurrent Networks
Justin Bayer, Christian Osendorfer
stat.MLcs.LGarXiv:1411.7610v32014
Generalized Nonconvex Nonsmooth Low-Rank Minimization
Canyi Lu, Jinhui Tang, Shuicheng Yan +1
cs.CVcs.LGstat.MLarXiv:1404.7306v12014
Monash Time Series Forecasting Archive
Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I. Webb +2
cs.LGstat.MLarXiv:2105.06643v12021
FinanceBench: A New Benchmark for Financial Question Answering
Pranab Islam, Anand Kannappan, Douwe Kiela +3
cs.CLcs.AIcs.CEarXiv:2311.11944v12023
Adversarial Self-Supervised Contrastive Learning
Minseon Kim, Jihoon Tack, Sung Ju Hwang
cs.LGcs.CVstat.MLarXiv:2006.07589v22020
RUDDER: Return Decomposition for Delayed Rewards
Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich +3
cs.LGcs.AImath.OCarXiv:1806.07857v32018
A Divergence Minimization Perspective on Imitation Learning Methods
Seyed Kamyar Seyed Ghasemipour, Richard Zemel, Shixiang Gu
cs.LGstat.MLarXiv:1911.02256v12019
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning
Jize Zhang, Bhavya Kailkhura, T. Yong-Jin Han
cs.LGstat.MLarXiv:2003.07329v22020
A Survey on Neural Architecture Search
Martin Wistuba, Ambrish Rawat, Tejaswini Pedapati
cs.LGcs.CVcs.NEarXiv:1905.01392v22019
Transfer learning for time series classification
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber +2
cs.LGcs.AIstat.MLarXiv:1811.01533v12018
Predicting the Computational Cost of Deep Learning Models
Daniel Justus, John Brennan, Stephen Bonner +1
cs.LGcs.AIstat.MLarXiv:1811.11880v12018
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
Milad Nasr, Reza Shokri, Amir Houmansadr
stat.MLcs.CRcs.LGarXiv:1812.00910v22018
Is Local SGD Better than Minibatch SGD?
Blake Woodworth, Kumar Kshitij Patel, Sebastian U. Stich +5
cs.LGmath.OCstat.MLarXiv:2002.07839v22020
Computing Graph Neural Networks: A Survey from Algorithms to Accelerators
Sergi Abadal, Akshay Jain, Robert Guirado +2
cs.LGcs.DCstat.MLarXiv:2010.00130v32020
Streaming Graph Neural Networks
Yao Ma, Ziyi Guo, Zhaochun Ren +3
cs.LGstat.MLarXiv:1810.10627v22018
Overcoming Forgetting in Federated Learning on Non-IID Data
Neta Shoham, Tomer Avidor, Aviv Keren +4
cs.LGcs.CRstat.MLarXiv:1910.07796v12019
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
Luigi Acerbi, Wei Ji Ma
stat.MLq-bio.NCq-bio.QMarXiv:1705.04405v22017
Reinforcement and Imitation Learning via Interactive No-Regret Learning
Stephane Ross, J. Andrew Bagnell
cs.LGstat.MLarXiv:1406.5979v12014
Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics
Arsenii Kuznetsov, Pavel Shvechikov, Alexander Grishin +1
cs.LGcs.AIstat.MLarXiv:2005.04269v12020
Model-Free Episodic Control
Charles Blundell, Benigno Uria, Alexander Pritzel +6
stat.MLcs.LGq-bio.NCarXiv:1606.04460v12016
Online Clustering of Bandits
Claudio Gentile, Shuai Li, Giovanni Zappella
cs.LGstat.MLarXiv:1401.8257v32014
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced
Simon S. Du, Wei Hu, Jason D. Lee
cs.LGmath.OCstat.MLarXiv:1806.00900v22018
Three Mechanisms of Weight Decay Regularization
Guodong Zhang, Chaoqi Wang, Bowen Xu +1
cs.LGstat.MLarXiv:1810.12281v12018
Rademacher Complexity for Adversarially Robust Generalization
Dong Yin, Kannan Ramchandran, Peter Bartlett
cs.LGcs.CRcs.NEarXiv:1810.11914v42018
Counterfactual Fairness in Text Classification through Robustness
Sahaj Garg, Vincent Perot, Nicole Limtiaco +3
cs.LGstat.MLarXiv:1809.10610v22018
Rectified Flow: A Marginal Preserving Approach to Optimal Transport
Qiang Liu
stat.MLcs.LGarXiv:2209.14577v12022
Augmentor: An Image Augmentation Library for Machine Learning
Marcus D. Bloice, Christof Stocker, Andreas Holzinger
cs.CVcs.LGstat.MLarXiv:1708.04680v12017
Episodic Curiosity through Reachability
Nikolay Savinov, Anton Raichuk, Raphaël Marinier +4
cs.LGcs.AIcs.CVarXiv:1810.02274v52018
Unlocking High-Accuracy Differentially Private Image Classification through Scale
Soham De, Leonard Berrada, Jamie Hayes +2
cs.LGcs.CRcs.CVarXiv:2204.13650v22022
Bayesian Neural Networks: An Introduction and Survey
Ethan Goan, Clinton Fookes
stat.MLcs.LGarXiv:2006.12024v32020
A statistical model for tensor PCA
Andrea Montanari, Emile Richard
cs.LGcs.ITstat.MLarXiv:1411.1076v12014
Stochastic Compositional Gradient Descent: Algorithms for Minimizing Compositions of Expected-Value Functions
Mengdi Wang, Ethan X. Fang, Han Liu
stat.MLarXiv:1411.3803v12014
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
Lars Ruthotto, Stanley Osher, Wuchen Li +2
cs.LGmath.NAmath.OCarXiv:1912.01825v32019
Transfer Learning with Dynamic Distribution Adaptation
Jindong Wang, Yiqiang Chen, Wenjie Feng +3
cs.LGstat.MLarXiv:1909.08531v12019
Equivariance Through Parameter-Sharing
Siamak Ravanbakhsh, Jeff Schneider, Barnabas Poczos
stat.MLcs.NEarXiv:1702.08389v22017
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
Yudong Chen, Lili Su, Jiaming Xu
cs.DCcs.CRcs.LGarXiv:1705.05491v22017
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds
Xiaohan Chen, Jialin Liu, Zhangyang Wang +1
cs.LGstat.MLarXiv:1808.10038v22018
Continual Unsupervised Representation Learning
Dushyant Rao, Francesco Visin, Andrei A. Rusu +3
cs.LGcs.AIcs.CVarXiv:1910.14481v12019
Dealing with Integer-valued Variables in Bayesian Optimization with Gaussian Processes
Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
stat.MLarXiv:1706.03673v22017
N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification
Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi +1
cs.LGcs.SIstat.MLarXiv:1802.08888v12018
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning
Yu Yao, Tongliang Liu, Bo Han +4
cs.LGstat.MLarXiv:2006.07805v32020
I$^2$SB: Image-to-Image Schrödinger Bridge
Guan-Horng Liu, Arash Vahdat, De-An Huang +3
cs.CVcs.LGstat.MLarXiv:2302.05872v32023
Robust Spectral Compressed Sensing via Structured Matrix Completion
Yuxin Chen, Yuejie Chi
cs.ITeess.SYmath.NAarXiv:1304.8126v52013
Physics-informed neural network for ultrasound nondestructive quantification of surface breaking cracks
Khemraj Shukla, Patricio Clark Di Leoni, James Blackshire +2
cs.LGstat.MLarXiv:2005.03596v12020
A Crowdsourcing Framework for On-Device Federated Learning
Shashi Raj Pandey, Nguyen H. Tran, Mehdi Bennis +3
cs.LGcs.GTcs.NIarXiv:1911.01046v22019
Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks
Kunjin Chen, Jun Hu, Yu Zhang +2
cs.LGstat.APstat.MLarXiv:1812.09464v22018
Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence
Mert Pilanci, Martin J. Wainwright
math.OCcs.DScs.LGarXiv:1505.02250v12015
TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks
Alexander Geiger, Dongyu Liu, Sarah Alnegheimish +2
cs.LGstat.MLarXiv:2009.07769v32020
Discovering Latent Network Structure in Point Process Data
Scott W. Linderman, Ryan P. Adams
stat.MLcs.LGarXiv:1402.0914v12014
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy
Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann +4
stat.MLcs.AIcs.LGarXiv:1611.04488v62016
RODE: Learning Roles to Decompose Multi-Agent Tasks
Tonghan Wang, Tarun Gupta, Anuj Mahajan +3
cs.LGstat.MLarXiv:2010.01523v12020
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization
Constantinos Daskalakis, Ioannis Panageas
math.OCcs.LGstat.MLarXiv:1807.03907v22018
Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation
Lu Wang, Wei Zhang, Xiaofeng He +1
cs.LGstat.MLarXiv:1807.01473v22018
Using Hindsight to Anchor Past Knowledge in Continual Learning
Arslan Chaudhry, Albert Gordo, Puneet K. Dokania +2
cs.LGstat.MLarXiv:2002.08165v22020
Hierarchical Transformers for Long Document Classification
Raghavendra Pappagari, Piotr Żelasko, Jesús Villalba +2
cs.CLcs.LGstat.MLarXiv:1910.10781v12019
Does provable absence of barren plateaus imply classical simulability?
M. Cerezo, Martin Larocca, Diego García-Martín +9
quant-phcs.LGstat.MLarXiv:2312.09121v32023
Deep Spectral Clustering using Dual Autoencoder Network
Xu Yang, Cheng Deng, Feng Zheng +2
cs.LGcs.CVstat.MLarXiv:1904.13113v12019
Causal Discovery with Reinforcement Learning
Shengyu Zhu, Ignavier Ng, Zhitang Chen
cs.LGstat.MLarXiv:1906.04477v42019
tinyBenchmarks: evaluating LLMs with fewer examples
Felipe Maia Polo, Lucas Weber, Leshem Choshen +3
cs.CLcs.AIcs.LGarXiv:2402.14992v22024

Machine Learning (stat)

Self-Distillation Amplifies Regularization in Hilbert Space

Learning Stochastic Recurrent Networks

Generalized Nonconvex Nonsmooth Low-Rank Minimization

Monash Time Series Forecasting Archive

FinanceBench: A New Benchmark for Financial Question Answering

Adversarial Self-Supervised Contrastive Learning

RUDDER: Return Decomposition for Delayed Rewards

A Divergence Minimization Perspective on Imitation Learning Methods

Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning

A Survey on Neural Architecture Search

Transfer learning for time series classification

Predicting the Computational Cost of Deep Learning Models

Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

Is Local SGD Better than Minibatch SGD?

Computing Graph Neural Networks: A Survey from Algorithms to Accelerators

Streaming Graph Neural Networks

Overcoming Forgetting in Federated Learning on Non-IID Data

Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search

Reinforcement and Imitation Learning via Interactive No-Regret Learning

Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics

Model-Free Episodic Control

Online Clustering of Bandits

Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced

Three Mechanisms of Weight Decay Regularization

Rademacher Complexity for Adversarially Robust Generalization

Counterfactual Fairness in Text Classification through Robustness

Rectified Flow: A Marginal Preserving Approach to Optimal Transport

Augmentor: An Image Augmentation Library for Machine Learning

Episodic Curiosity through Reachability

Unlocking High-Accuracy Differentially Private Image Classification through Scale

Bayesian Neural Networks: An Introduction and Survey

A statistical model for tensor PCA

Stochastic Compositional Gradient Descent: Algorithms for Minimizing Compositions of Expected-Value Functions

A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems

Transfer Learning with Dynamic Distribution Adaptation

Equivariance Through Parameter-Sharing

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent

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

Continual Unsupervised Representation Learning

Dealing with Integer-valued Variables in Bayesian Optimization with Gaussian Processes

N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification

Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning

I$^2$SB: Image-to-Image Schrödinger Bridge

Robust Spectral Compressed Sensing via Structured Matrix Completion

Physics-informed neural network for ultrasound nondestructive quantification of surface breaking cracks

A Crowdsourcing Framework for On-Device Federated Learning

Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks

Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks

Discovering Latent Network Structure in Point Process Data

Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy

RODE: Learning Roles to Decompose Multi-Agent Tasks

The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization

Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation

Using Hindsight to Anchor Past Knowledge in Continual Learning

Hierarchical Transformers for Long Document Classification

Does provable absence of barren plateaus imply classical simulability?

Deep Spectral Clustering using Dual Autoencoder Network

Causal Discovery with Reinforcement Learning

tinyBenchmarks: evaluating LLMs with fewer examples