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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1,021 to 1,080 of 6,798

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
Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
Ying Wen, Yaodong Yang, Rui Luo +2
cs.LGcs.AIstat.MLarXiv:1901.09207v22019
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions
Amar Shah, Zoubin Ghahramani
cs.LGstat.MLarXiv:1511.07130v12015
Lorentz Group Equivariant Neural Network for Particle Physics
Alexander Bogatskiy, Brandon Anderson, Jan T. Offermann +3
hep-phcs.LGhep-exarXiv:2006.04780v12020
Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks
Yuan Cao, Quanquan Gu
cs.LGmath.OCstat.MLarXiv:1902.01384v42019
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search
Lars Buesing, Theophane Weber, Yori Zwols +4
cs.LGstat.MLarXiv:1811.06272v12018
Deep Signature Transforms
Patric Bonnier, Patrick Kidger, Imanol Perez Arribas +2
cs.LGstat.MLarXiv:1905.08494v22019
Boosting Adversarial Training with Hypersphere Embedding
Tianyu Pang, Xiao Yang, Yinpeng Dong +3
cs.LGcs.CRcs.CVarXiv:2002.08619v32020
General-purpose Tagging of Freesound Audio with AudioSet Labels: Task Description, Dataset, and Baseline
Eduardo Fonseca, Manoj Plakal, Frederic Font +4
cs.SDcs.LGeess.ASarXiv:1807.09902v32018
A Topology Layer for Machine Learning
Rickard Brüel-Gabrielsson, Bradley J. Nelson, Anjan Dwaraknath +3
cs.LGmath.ATstat.MLarXiv:1905.12200v22019
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki +3
stat.MLcs.LGmath.STarXiv:2205.01445v12022
Generalized Shape Metrics on Neural Representations
Alex H. Williams, Erin Kunz, Simon Kornblith +1
stat.MLcs.LGarXiv:2110.14739v22021
Multi-Agent Adversarial Inverse Reinforcement Learning
Lantao Yu, Jiaming Song, Stefano Ermon
cs.LGstat.MLarXiv:1907.13220v12019
Semismooth Newton Coordinate Descent Algorithm for Elastic-Net Penalized Huber Loss Regression and Quantile Regression
Congrui Yi, Jian Huang
stat.COstat.MLarXiv:1509.02957v22015
Interpretation and Generalization of Score Matching
Siwei Lyu
cs.LGstat.MLarXiv:1205.2629v12012
Distributionally Robust Federated Averaging
Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi
cs.LGcs.DCstat.MLarXiv:2102.12660v12021
Robust Regression via Hard Thresholding
Kush Bhatia, Prateek Jain, Purushottam Kar
cs.LGstat.MLarXiv:1506.02428v12015
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset
Muhammad Waleed Gondal, Manuel Wüthrich, Đorđe Miladinović +7
stat.MLcs.LGarXiv:1906.03292v32019
Geometric Understanding of Deep Learning
Na Lei, Zhongxuan Luo, Shing-Tung Yau +1
cs.LGstat.MLarXiv:1805.10451v22018
Unsupervised Depth Completion from Visual Inertial Odometry
Alex Wong, Xiaohan Fei, Stephanie Tsuei +1
cs.CVcs.AIcs.LGarXiv:1905.08616v42019
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search
Binghong Chen, Chengtao Li, Hanjun Dai +1
cs.LGcs.AIstat.MLarXiv:2006.15820v12020
Shape-Based Approach to Household Load Curve Clustering and Prediction
Thanchanok Teeraratkul, Daniel O'Neill, Sanjay Lall
stat.MLarXiv:1702.01414v12017
Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Dataset
Dimitrios Kollias, Stefanos Zafeiriou
cs.LGcs.CVstat.MLarXiv:1910.01417v22019
How Perturbations Propagate: A Multi-Level Analysis of Robustness in Large Language Models
Dun Li Chan, Emily Liu, Niyathi Allu +1
cs.CLstat.MLarXiv:2609.03322v12026
Optimal Transport for Multi-source Domain Adaptation under Target Shift
Ievgen Redko, Nicolas Courty, Rémi Flamary +1
stat.MLarXiv:1803.04899v32018
Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms
Christopher De Sa, Ce Zhang, Kunle Olukotun +1
cs.LGmath.OCstat.MLarXiv:1506.06438v22015
Summaries:한국어
Efficient Algorithms for Outlier-Robust Regression
Adam Klivans, Pravesh K. Kothari, Raghu Meka
cs.LGcs.AIcs.DSarXiv:1803.03241v32018
Stochastic Latent Residual Video Prediction
Jean-Yves Franceschi, Edouard Delasalles, Mickaël Chen +2
cs.CVcs.LGstat.MLarXiv:2002.09219v42020
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Kaidi Xu, Sijia Liu, Pu Zhao +6
cs.LGcs.AIstat.MLarXiv:1808.01664v32018
MAP Estimation, Linear Programming and Belief Propagation with Convex Free Energies
Yair Weiss, Chen Yanover, Talya Meltzer
cs.AIcs.LGstat.MLarXiv:1206.5286v12012
Neural Network Attributions: A Causal Perspective
Aditya Chattopadhyay, Piyushi Manupriya, Anirban Sarkar +1
cs.LGstat.MLarXiv:1902.02302v42019
PU Learning for Matrix Completion
Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon
cs.LGmath.NAstat.MLarXiv:1411.6081v12014
How Do Classifiers Induce Agents To Invest Effort Strategically?
Jon Kleinberg, Manish Raghavan
cs.LGcs.CYcs.DSarXiv:1807.05307v52018
Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints
Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa
cs.LGcs.AIstat.MLarXiv:2009.01721v22020
Finite Sample Analysis of Stochastic System Identification
Anastasios Tsiamis, George J. Pappas
cs.LGeess.SYmath.OCarXiv:1903.09122v12019
Deepcode: Feedback Codes via Deep Learning
Hyeji Kim, Yihan Jiang, Sreeram Kannan +2
cs.LGcs.ITstat.MLarXiv:1807.00801v12018
RES: Regularized Stochastic BFGS Algorithm
Aryan Mokhtari, Alejandro Ribeiro
cs.LGmath.OCstat.MLarXiv:1401.7625v12014
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases
Ren Wang, Gaoyuan Zhang, Sijia Liu +3
cs.LGcs.CRstat.MLarXiv:2007.15802v12020
Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs
Dávid Pál, Barnabás Póczos, Csaba Szepesvári
stat.MLcs.AIarXiv:1003.1954v22010
Fast Two-Sample Testing with Analytic Representations of Probability Measures
Kacper Chwialkowski, Aaditya Ramdas, Dino Sejdinovic +1
stat.MLarXiv:1506.04725v12015
Conservative Safety Critics for Exploration
Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart +3
cs.LGcs.AIcs.ROarXiv:2010.14497v22020
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
Yugeng Liu, Rui Wen, Xinlei He +6
cs.CRcs.AIcs.LGarXiv:2102.02551v22021
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback
Adith Swaminathan, Thorsten Joachims
cs.LGstat.MLarXiv:1502.02362v22015
ROP: Matrix recovery via rank-one projections
T. Tony Cai, Anru Zhang
math.STcs.ITstat.MEarXiv:1310.5791v32013
The probability flow ODE is provably fast
Sitan Chen, Sinho Chewi, Holden Lee +3
cs.LGmath.STstat.MLarXiv:2305.11798v12023
Fast $ε$-free Inference of Simulation Models with Bayesian Conditional Density Estimation
George Papamakarios, Iain Murray
stat.MLcs.LGstat.COarXiv:1605.06376v42016
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators
Changyou Chen, Nan Ding, Lawrence Carin
stat.MLarXiv:1610.06665v12016
Pre-training via Denoising for Molecular Property Prediction
Sheheryar Zaidi, Michael Schaarschmidt, James Martens +6
cs.LGq-bio.BMstat.MLarXiv:2206.00133v22022
GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Taha Aksu, Gerald Woo, Juncheng Liu +5
cs.LGstat.MLarXiv:2410.10393v22024
Personalized and Private Peer-to-Peer Machine Learning
Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki +1
cs.LGcs.CRcs.DCarXiv:1705.08435v22017
Deep Clustering and Conventional Networks for Music Separation: Stronger Together
Yi Luo, Zhuo Chen, John R. Hershey +2
stat.MLcs.LGcs.SDarXiv:1611.06265v22016
Optimal Rates For Regularization Of Statistical Inverse Learning Problems
Gilles Blanchard, Nicole Mücke
stat.MLarXiv:1604.04054v12016
Statistical Inference for Model Parameters in Stochastic Gradient Descent
Xi Chen, Jason D. Lee, Xin T. Tong +1
stat.MLarXiv:1610.08637v42016
Crime prediction through urban metrics and statistical learning
Luiz G A Alves, Haroldo V Ribeiro, Francisco A Rodrigues
physics.soc-phstat.APstat.MLarXiv:1712.03834v22017
Graph Neural Networks in TensorFlow and Keras with Spektral
Daniele Grattarola, Cesare Alippi
cs.LGstat.MLarXiv:2006.12138v12020

Machine Learning (stat)

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

Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning

Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions

Lorentz Group Equivariant Neural Network for Particle Physics

Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks

Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search

Deep Signature Transforms

Boosting Adversarial Training with Hypersphere Embedding

General-purpose Tagging of Freesound Audio with AudioSet Labels: Task Description, Dataset, and Baseline

A Topology Layer for Machine Learning

High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation

Generalized Shape Metrics on Neural Representations

Multi-Agent Adversarial Inverse Reinforcement Learning

Semismooth Newton Coordinate Descent Algorithm for Elastic-Net Penalized Huber Loss Regression and Quantile Regression

Interpretation and Generalization of Score Matching

Distributionally Robust Federated Averaging

Robust Regression via Hard Thresholding

On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset

Geometric Understanding of Deep Learning

Unsupervised Depth Completion from Visual Inertial Odometry

Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search

Shape-Based Approach to Household Load Curve Clustering and Prediction

Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Dataset

How Perturbations Propagate: A Multi-Level Analysis of Robustness in Large Language Models

Optimal Transport for Multi-source Domain Adaptation under Target Shift

Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms

Efficient Algorithms for Outlier-Robust Regression

Stochastic Latent Residual Video Prediction

Structured Adversarial Attack: Towards General Implementation and Better Interpretability

MAP Estimation, Linear Programming and Belief Propagation with Convex Free Energies

Neural Network Attributions: A Causal Perspective

PU Learning for Matrix Completion

How Do Classifiers Induce Agents To Invest Effort Strategically?

Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints

Finite Sample Analysis of Stochastic System Identification

Deepcode: Feedback Codes via Deep Learning

RES: Regularized Stochastic BFGS Algorithm

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases

Estimation of Rényi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs

Fast Two-Sample Testing with Analytic Representations of Probability Measures

Conservative Safety Critics for Exploration

ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models

Counterfactual Risk Minimization: Learning from Logged Bandit Feedback

ROP: Matrix recovery via rank-one projections

The probability flow ODE is provably fast

Fast $ε$-free Inference of Simulation Models with Bayesian Conditional Density Estimation

On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators

Pre-training via Denoising for Molecular Property Prediction

GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation

Personalized and Private Peer-to-Peer Machine Learning

Deep Clustering and Conventional Networks for Music Separation: Stronger Together

Optimal Rates For Regularization Of Statistical Inverse Learning Problems

Statistical Inference for Model Parameters in Stochastic Gradient Descent

Crime prediction through urban metrics and statistical learning

Graph Neural Networks in TensorFlow and Keras with Spektral

Retro: Learning Retrosynthetic Planning with Neural Guided A Search