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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961 to 1,020 of 6,792

Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo +2
cs.LGcs.AIstat.MLarXiv:2006.03647v22020
Stochastic Nested Variance Reduction for Nonconvex Optimization
Dongruo Zhou, Pan Xu, Quanquan Gu
cs.LGmath.OCstat.MLarXiv:1806.07811v22018
Rethinking the Expressive Power of GNNs via Graph Biconnectivity
Bohang Zhang, Shengjie Luo, Liwei Wang +1
cs.LGstat.MLarXiv:2301.09505v32023
Stagewise Safe Bayesian Optimization with Gaussian Processes
Yanan Sui, Vincent Zhuang, Joel W. Burdick +1
cs.LGstat.MLarXiv:1806.07555v22018
Speaker Anonymization Using X-vector and Neural Waveform Models
Fuming Fang, Xin Wang, Junichi Yamagishi +4
eess.AScs.CLcs.LGarXiv:1905.13561v12019
Learning to Continually Learn
Shawn Beaulieu, Lapo Frati, Thomas Miconi +4
cs.LGcs.CVcs.NEarXiv:2002.09571v22020
Putting An End to End-to-End: Gradient-Isolated Learning of Representations
Sindy Löwe, Peter O'Connor, Bastiaan S. Veeling
cs.LGcs.AIstat.MLarXiv:1905.11786v32019
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
Dongruo Zhou, Jinghui Chen, Yuan Cao +2
cs.LGmath.OCstat.MLarXiv:1808.05671v42018
Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning
Zhiyuan Li, Yuping Luo, Kaifeng Lyu
cs.LGstat.MLarXiv:2012.09839v22020
Convergence Analysis for Rectangular Matrix Completion Using Burer-Monteiro Factorization and Gradient Descent
Qinqing Zheng, John Lafferty
stat.MLcs.LGarXiv:1605.07051v22016
Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization
Julien Mairal
stat.MLcs.LGmath.OCarXiv:1306.4650v22013
Operation-Aware Soft Channel Pruning using Differentiable Masks
Minsoo Kang, Bohyung Han
cs.LGcs.CVstat.MLarXiv:2007.03938v22020
Deep Generalized Canonical Correlation Analysis
Adrian Benton, Huda Khayrallah, Biman Gujral +3
cs.LGcs.AIstat.MLarXiv:1702.02519v22017
Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory
Adel Javanmard, Andrea Montanari
stat.MEcs.ITmath.STarXiv:1301.4240v32013
Conditional mean embeddings as regressors - supplementary
Steffen Grünewälder, Guy Lever, Luca Baldassarre +3
cs.LGstat.MLarXiv:1205.4656v22012
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs
Max Simchowitz, Kevin Jamieson
cs.LGmath.OCmath.STarXiv:1905.03814v22019
Compound Probabilistic Context-Free Grammars for Grammar Induction
Yoon Kim, Chris Dyer, Alexander M. Rush
cs.CLstat.MLarXiv:1906.10225v92019
Summaries:한국어
Online Alternating Direction Method
Huahua Wang, Arindam Banerjee
cs.LGstat.MLarXiv:1206.6448v12012
Sparse Prediction with the $k$-Support Norm
Andreas Argyriou, Rina Foygel, Nathan Srebro
stat.MLcs.LGarXiv:1204.5043v22012
Extraction of Pharmacokinetic Evidence of Drug-drug Interactions from the Literature
Artemy Kolchinsky, Anália Lourenço, Heng-Yi Wu +2
stat.MLcs.IRq-bio.QMarXiv:1412.0744v22014
Machine Learning in the Search for New Fundamental Physics
Georgia Karagiorgi, Gregor Kasieczka, Scott Kravitz +2
hep-phhep-exphysics.data-anarXiv:2112.03769v12021
DPM: A deep learning PDE augmentation method (with application to large-eddy simulation)
Jonathan B. Freund, Jonathan F. MacArt, Justin Sirignano
cs.LGcs.CEstat.MLarXiv:1911.09145v12019
Geometry- and Accuracy-Preserving Random Forest Proximities
Jake S. Rhodes, Adele Cutler, Kevin R. Moon
stat.MLcs.LGstat.AParXiv:2201.12682v22022
SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties
Garrett B. Goh, Nathan O. Hodas, Charles Siegel +1
stat.MLcs.AIcs.CLarXiv:1712.02034v22017
DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting
Xiangfei Qiu, Xingjian Wu, Yan Lin +3
cs.LGstat.MLarXiv:2412.10859v32024
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
Boris van Breugel, Trent Kyono, Jeroen Berrevoets +1
cs.LGstat.MLarXiv:2110.12884v22021
Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples
Guanhong Tao, Shiqing Ma, Yingqi Liu +1
cs.LGcs.AIcs.CRarXiv:1810.11580v12018
Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards
Haoxiang Wang, Yong Lin, Wei Xiong +5
cs.LGcs.AIcs.CLarXiv:2402.18571v32024
Generalized Inner Loop Meta-Learning
Edward Grefenstette, Brandon Amos, Denis Yarats +6
cs.LGstat.MLarXiv:1910.01727v22019
Omega-Regular Objectives in Model-Free Reinforcement Learning
Ernst Moritz Hahn, Mateo Perez, Sven Schewe +3
cs.LOcs.LGstat.MLarXiv:1810.00950v12018
Deep Learning for Reflected BSDEs: Regularization and Error Analysis
Ruimeng Hu, Yihan Zou
q-fin.CPstat.MLarXiv:2609.05434v12026
Linear dynamical neural population models through nonlinear embeddings
Yuanjun Gao, Evan Archer, Liam Paninski +1
q-bio.NCstat.MLarXiv:1605.08454v22016
QMDP-Net: Deep Learning for Planning under Partial Observability
Peter Karkus, David Hsu, Wee Sun Lee
cs.AIcs.LGcs.NEarXiv:1703.06692v32017
Graph Structure of Neural Networks
Jiaxuan You, Jure Leskovec, Kaiming He +1
cs.LGcs.CVcs.SIarXiv:2007.06559v22020
Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning
Sheng Wan, Shirui Pan, Jian Yang +1
cs.LGstat.MLarXiv:2009.07111v22020
DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System
Zhi-Hong Deng, Ling Huang, Chang-Dong Wang +2
cs.LGcs.IRstat.MLarXiv:1901.04704v12019
Are All Layers Created Equal?
Chiyuan Zhang, Samy Bengio, Yoram Singer
stat.MLcs.AIcs.LGarXiv:1902.01996v42019
Towards Deeper Understanding of Variational Autoencoding Models
Shengjia Zhao, Jiaming Song, Stefano Ermon
cs.LGstat.MLarXiv:1702.08658v12017
Measuring and regularizing networks in function space
Ari S. Benjamin, David Rolnick, Konrad Kording
cs.NEcs.LGstat.MLarXiv:1805.08289v32018
Improved Consistency Regularization for GANs
Zhengli Zhao, Sameer Singh, Honglak Lee +3
stat.MLcs.LGarXiv:2002.04724v22020
McGan: Mean and Covariance Feature Matching GAN
Youssef Mroueh, Tom Sercu, Vaibhava Goel
cs.LGstat.MLarXiv:1702.08398v22017
Understanding and correcting pathologies in the training of learned optimizers
Luke Metz, Niru Maheswaranathan, Jeremy Nixon +2
cs.NEstat.MLarXiv:1810.10180v52018
Online Linear Quadratic Control
Alon Cohen, Avinatan Hassidim, Tomer Koren +3
cs.LGstat.MLarXiv:1806.07104v12018
Covariate-assisted spectral clustering
Norbert Binkiewicz, Joshua T. Vogelstein, Karl Rohe
stat.MLcs.LGmath.STarXiv:1411.2158v52014
Rates of Convergence for Sparse Variational Gaussian Process Regression
David R. Burt, Carl E. Rasmussen, Mark van der Wilk
stat.MLcs.LGarXiv:1903.03571v32019
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning
Kimin Lee, Younggyo Seo, Seunghyun Lee +2
cs.LGstat.MLarXiv:2005.06800v32020
Efficient Bayesian Inference for Generalized Bradley-Terry Models
Francois Caron, Arnaud Doucet
stat.MEstat.COstat.MLarXiv:1011.1761v12010
Random Reshuffling: Simple Analysis with Vast Improvements
Konstantin Mishchenko, Ahmed Khaled, Peter Richtárik
math.OCcs.LGstat.MLarXiv:2006.05988v32020
The Feature Importance Ranking Measure
Alexander Zien, Nicole Kraemer, Soeren Sonnenburg +1
stat.MLarXiv:0906.4258v12009
Proximal Algorithms in Statistics and Machine Learning
Nicholas G. Polson, James G. Scott, Brandon T. Willard
stat.MLcs.LGstat.MEarXiv:1502.03175v32015
Sales Demand Forecast in E-commerce using a Long Short-Term Memory Neural Network Methodology
Kasun Bandara, Peibei Shi, Christoph Bergmeir +3
cs.LGstat.MLarXiv:1901.04028v22019
The Proper Care and Feeding of CAMELS: How Limited Training Data Affects Streamflow Prediction
Martin Gauch, Juliane Mai, Jimmy Lin
cs.LGstat.MLarXiv:1911.07249v32019
Continual Learning with Node-Importance based Adaptive Group Sparse Regularization
Sangwon Jung, Hongjoon Ahn, Sungmin Cha +1
cs.LGstat.MLarXiv:2003.13726v42020
CapsuleGAN: Generative Adversarial Capsule Network
Ayush Jaiswal, Wael AbdAlmageed, Yue Wu +1
stat.MLcs.LGarXiv:1802.06167v72018
Real-time Faulted Line Localization and PMU Placement in Power Systems through Convolutional Neural Networks
Wenting Li, Deepjyoti Deka, Michael Chertkov +1
eess.SYcs.LGstat.MLarXiv:1810.05247v22018
Sparse DNNs with Improved Adversarial Robustness
Yiwen Guo, Chao Zhang, Changshui Zhang +1
cs.LGcs.CRcs.CVarXiv:1810.09619v22018
Strategies and Principles of Distributed Machine Learning on Big Data
Eric P. Xing, Qirong Ho, Pengtao Xie +1
stat.MLcs.DCcs.LGarXiv:1512.09295v12015
Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
Zixin Wen, Yuanzhi Li
cs.LGcs.CVstat.MLarXiv:2105.15134v32021
Word2Vec applied to Recommendation: Hyperparameters Matter
Hugo Caselles-Dupré, Florian Lesaint, Jimena Royo-Letelier
cs.IRcs.CLcs.LGarXiv:1804.04212v32018
On Robustness of Neural Ordinary Differential Equations
Hanshu Yan, Jiawei Du, Vincent Y. F. Tan +1
cs.LGstat.MLarXiv:1910.05513v42019

Machine Learning (stat)

Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization

Stochastic Nested Variance Reduction for Nonconvex Optimization

Rethinking the Expressive Power of GNNs via Graph Biconnectivity

Stagewise Safe Bayesian Optimization with Gaussian Processes

Speaker Anonymization Using X-vector and Neural Waveform Models

Learning to Continually Learn

Putting An End to End-to-End: Gradient-Isolated Learning of Representations

On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning

Convergence Analysis for Rectangular Matrix Completion Using Burer-Monteiro Factorization and Gradient Descent

Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization

Operation-Aware Soft Channel Pruning using Differentiable Masks

Deep Generalized Canonical Correlation Analysis

Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory

Conditional mean embeddings as regressors - supplementary

Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs

Compound Probabilistic Context-Free Grammars for Grammar Induction

Online Alternating Direction Method

Sparse Prediction with the $k$-Support Norm

Extraction of Pharmacokinetic Evidence of Drug-drug Interactions from the Literature

Machine Learning in the Search for New Fundamental Physics

DPM: A deep learning PDE augmentation method (with application to large-eddy simulation)

Geometry- and Accuracy-Preserving Random Forest Proximities

SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting

DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks

Attacks Meet Interpretability: Attribute-steered Detection of Adversarial Samples

Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards

Generalized Inner Loop Meta-Learning

Omega-Regular Objectives in Model-Free Reinforcement Learning

Deep Learning for Reflected BSDEs: Regularization and Error Analysis

Linear dynamical neural population models through nonlinear embeddings

QMDP-Net: Deep Learning for Planning under Partial Observability

Graph Structure of Neural Networks

Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning

DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System

Are All Layers Created Equal?

Towards Deeper Understanding of Variational Autoencoding Models

Measuring and regularizing networks in function space

Improved Consistency Regularization for GANs

McGan: Mean and Covariance Feature Matching GAN

Understanding and correcting pathologies in the training of learned optimizers

Online Linear Quadratic Control

Covariate-assisted spectral clustering

Rates of Convergence for Sparse Variational Gaussian Process Regression

Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning

Efficient Bayesian Inference for Generalized Bradley-Terry Models

Random Reshuffling: Simple Analysis with Vast Improvements

The Feature Importance Ranking Measure

Proximal Algorithms in Statistics and Machine Learning

Sales Demand Forecast in E-commerce using a Long Short-Term Memory Neural Network Methodology

The Proper Care and Feeding of CAMELS: How Limited Training Data Affects Streamflow Prediction

Continual Learning with Node-Importance based Adaptive Group Sparse Regularization

CapsuleGAN: Generative Adversarial Capsule Network

Real-time Faulted Line Localization and PMU Placement in Power Systems through Convolutional Neural Networks

Sparse DNNs with Improved Adversarial Robustness

Strategies and Principles of Distributed Machine Learning on Big Data

Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning

Word2Vec applied to Recommendation: Hyperparameters Matter

On Robustness of Neural Ordinary Differential Equations