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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3,361 to 3,420 of 6,785

Dynamic Word Embeddings
Robert Bamler, Stephan Mandt
stat.MLcs.LGarXiv:1702.08359v22017
LanczosNet: Multi-Scale Deep Graph Convolutional Networks
Renjie Liao, Zhizhen Zhao, Raquel Urtasun +1
cs.LGstat.MLarXiv:1901.01484v22019
Compressed Sensing of EEG for Wireless Telemonitoring with Low Energy Consumption and Inexpensive Hardware
Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig +1
stat.APcs.ITstat.MLarXiv:1206.3493v32012
On the Accuracy of Influence Functions for Measuring Group Effects
Pang Wei Koh, Kai-Siang Ang, Hubert H. K. Teo +1
cs.LGstat.MLarXiv:1905.13289v22019
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics
Yuchen Zhang, Percy Liang, Moses Charikar
cs.LGmath.OCstat.MLarXiv:1702.05575v32017
Training independent subnetworks for robust prediction
Marton Havasi, Rodolphe Jenatton, Stanislav Fort +5
cs.LGcs.CVstat.MLarXiv:2010.06610v22020
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization
Jian Wu, Peter I. Frazier
stat.MLcs.AIcs.LGarXiv:1606.04414v42016
Iterative PET Image Reconstruction Using Convolutional Neural Network Representation
Kuang Gong, Jiahui Guan, Kyungsang Kim +4
cs.CVphysics.med-phstat.MLarXiv:1710.03344v12017
On the convergence properties of a $K$-step averaging stochastic gradient descent algorithm for nonconvex optimization
Fan Zhou, Guojing Cong
cs.LGcs.DCstat.MLarXiv:1708.01012v32017
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
Lam M. Nguyen, Phuong Ha Nguyen, Marten van Dijk +3
math.OCcs.LGstat.MLarXiv:1802.03801v22018
A state-space mixed membership blockmodel for dynamic network tomography
Eric P. Xing, Wenjie Fu, Le Song
stat.MLq-bio.MNq-bio.QMarXiv:0901.0135v22008
Tile2Vec: Unsupervised representation learning for spatially distributed data
Neal Jean, Sherrie Wang, Anshul Samar +3
cs.CVcs.LGstat.MLarXiv:1805.02855v22018
Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget
Anoop Korattikara, Yutian Chen, Max Welling
cs.LGstat.MLarXiv:1304.5299v42013
Adaptive Machine Unlearning
Varun Gupta, Christopher Jung, Seth Neel +3
cs.LGstat.MLarXiv:2106.04378v12021
Apprenticeship Learning using Inverse Reinforcement Learning and Gradient Methods
Gergely Neu, Csaba Szepesvari
cs.LGstat.MLarXiv:1206.5264v12012
Relative Density-Ratio Estimation for Robust Distribution Comparison
Makoto Yamada, Taiji Suzuki, Takafumi Kanamori +2
stat.MLmath.STstat.MEarXiv:1106.4729v12011
Branch and Bound for Piecewise Linear Neural Network Verification
Rudy Bunel, Jingyue Lu, Ilker Turkaslan +3
cs.LGcs.LOstat.MLarXiv:1909.06588v52019
Orthogonal Random Features
Felix X. Yu, Ananda Theertha Suresh, Krzysztof Choromanski +2
cs.LGstat.MLarXiv:1610.09072v12016
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation
Matthew O'Kelly, Aman Sinha, Hongseok Namkoong +2
cs.LGcs.ROstat.MLarXiv:1811.00145v32018
Exact and Stable Covariance Estimation from Quadratic Sampling via Convex Programming
Yuxin Chen, Yuejie Chi, Andrea Goldsmith
cs.ITcs.LGmath.NAarXiv:1310.0807v52013
Spectral Graph Convolutions for Population-based Disease Prediction
Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante +4
stat.MLcs.LGarXiv:1703.03020v32017
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations
Ioana Bica, Ahmed M. Alaa, James Jordon +1
cs.LGstat.MLarXiv:2002.04083v12020
Deep Embedded Multi-view Clustering with Collaborative Training
Jie Xu, Yazhou Ren, Guofeng Li +3
cs.LGstat.MLarXiv:2007.13067v12020
Topology and Geometry of Half-Rectified Network Optimization
C. Daniel Freeman, Joan Bruna
stat.MLcs.LGarXiv:1611.01540v42016
Degenerate Feedback Loops in Recommender Systems
Ray Jiang, Silvia Chiappa, Tor Lattimore +2
stat.MLcs.LGarXiv:1902.10730v32019
The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?
Roberto Calandra, Andrew Owens, Manu Upadhyaya +4
cs.ROcs.CVcs.LGarXiv:1710.05512v22017
Generative replay with feedback connections as a general strategy for continual learning
Gido M. van de Ven, Andreas S. Tolias
cs.LGcs.AIcs.CVarXiv:1809.10635v22018
CXPlain: Causal Explanations for Model Interpretation under Uncertainty
Patrick Schwab, Walter Karlen
cs.LGstat.MLarXiv:1910.12336v12019
giotto-tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration
Guillaume Tauzin, Umberto Lupo, Lewis Tunstall +6
cs.LGmath.ATstat.MLarXiv:2004.02551v22020
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
Adji B. Dieng, Chong Wang, Jianfeng Gao +1
cs.CLcs.AIcs.LGarXiv:1611.01702v22016
Controlling Fairness and Bias in Dynamic Learning-to-Rank
Marco Morik, Ashudeep Singh, Jessica Hong +1
cs.IRcs.CYstat.MLarXiv:2005.14713v12020
Lasso Screening Rules via Dual Polytope Projection
Jie Wang, Peter Wonka, Jieping Ye
cs.LGstat.MLarXiv:1211.3966v32012
Measuring Sample Quality with Stein's Method
Jackson Gorham, Lester Mackey
stat.MLcs.LGmath.PRarXiv:1506.03039v62015
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li +3
cs.LGstat.MLarXiv:2402.02368v32024
Invariant Representations without Adversarial Training
Daniel Moyer, Shuyang Gao, Rob Brekelmans +2
cs.LGstat.MLarXiv:1805.09458v42018
Perturbed Iterate Analysis for Asynchronous Stochastic Optimization
Horia Mania, Xinghao Pan, Dimitris Papailiopoulos +3
stat.MLcs.DCcs.DSarXiv:1507.06970v22015
On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products
Kush R. Varshney, Homa Alemzadeh
cs.CYstat.MLarXiv:1610.01256v22016
Decentralized Collaborative Learning of Personalized Models over Networks
Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi
cs.LGcs.AIcs.DCarXiv:1610.05202v22016
Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction
Nina Grgić-Hlača, Elissa M. Redmiles, Krishna P. Gummadi +1
stat.MLcs.CYcs.LGarXiv:1802.09548v12018
RKT : Relation-Aware Self-Attention for Knowledge Tracing
Shalini Pandey, Jaideep Srivastava
cs.LGcs.AIstat.MLarXiv:2008.12736v12020
Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision
Kuan Fang, Yuke Zhu, Animesh Garg +4
cs.ROcs.CVcs.LGarXiv:1806.09266v12018
Unsupervised Domain Adaptation through Self-Supervision
Yu Sun, Eric Tzeng, Trevor Darrell +1
cs.LGcs.CVstat.MLarXiv:1909.11825v22019
Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance
Giles Hooker, Lucas Mentch, Siyu Zhou
stat.MEcs.LGstat.MLarXiv:1905.03151v22019
On the Fairness of Disentangled Representations
Francesco Locatello, Gabriele Abbati, Tom Rainforth +3
cs.LGstat.MLarXiv:1905.13662v22019
A Survey of Reinforcement Learning Algorithms for Dynamically Varying Environments
Sindhu Padakandla
cs.LGcs.AIstat.MLarXiv:2005.10619v12020
Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multi-Layer Calorimeters
Michela Paganini, Luke de Oliveira, Benjamin Nachman
hep-exhep-phstat.MLarXiv:1705.02355v22017
Learning Granger Causality for Hawkes Processes
Hongteng Xu, Mehrdad Farajtabar, Hongyuan Zha
cs.LGstat.MLarXiv:1602.04511v22016
Policy Learning for Fairness in Ranking
Ashudeep Singh, Thorsten Joachims
cs.LGcs.CYcs.IRarXiv:1902.04056v22019
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale +4
cs.LGcs.DCmath.OCarXiv:2008.03606v22020
Non-asymptotic Identification of LTI Systems from a Single Trajectory
Samet Oymak, Necmiye Ozay
cs.LGeess.SYmath.OCarXiv:1806.05722v22018
Imitation Learning via Off-Policy Distribution Matching
Ilya Kostrikov, Ofir Nachum, Jonathan Tompson
cs.LGstat.MLarXiv:1912.05032v12019
On Iterative Hard Thresholding Methods for High-dimensional M-Estimation
Prateek Jain, Ambuj Tewari, Purushottam Kar
cs.LGstat.MLarXiv:1410.5137v22014
Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and Simplicity
Dong Huang, Chang-Dong Wang, Jian-Huang Lai
cs.LGstat.MLarXiv:2203.11572v42022
A Close Look at Deep Learning with Small Data
L. Brigato, L. Iocchi
cs.LGstat.MLarXiv:2003.12843v32020
Unifying Human and Statistical Evaluation for Natural Language Generation
Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang
cs.CLcs.AIstat.MLarXiv:1904.02792v12019
Data Valuation using Reinforcement Learning
Jinsung Yoon, Sercan O. Arik, Tomas Pfister
cs.LGstat.MLarXiv:1909.11671v12019
Making deep neural networks right for the right scientific reasons by interacting with their explanations
Patrick Schramowski, Wolfgang Stammer, Stefano Teso +5
cs.LGcs.AIstat.MLarXiv:2001.05371v42020
Learning image representations tied to ego-motion
Dinesh Jayaraman, Kristen Grauman
cs.CVcs.AIstat.MLarXiv:1505.02206v22015
Deep Reinforcement Learning for Swarm Systems
Maximilian Hüttenrauch, Adrian Šošić, Gerhard Neumann
cs.MAcs.AIcs.LGarXiv:1807.06613v32018
Multi-output Bus Travel Time Prediction with Convolutional LSTM Neural Network
Niklas Christoffer Petersen, Filipe Rodrigues, Francisco Camara Pereira
stat.MLcs.LGarXiv:1903.02791v12019

Machine Learning (stat)

Dynamic Word Embeddings

LanczosNet: Multi-Scale Deep Graph Convolutional Networks

Compressed Sensing of EEG for Wireless Telemonitoring with Low Energy Consumption and Inexpensive Hardware

On the Accuracy of Influence Functions for Measuring Group Effects

A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics

Training independent subnetworks for robust prediction

The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

Iterative PET Image Reconstruction Using Convolutional Neural Network Representation

On the convergence properties of a $K$-step averaging stochastic gradient descent algorithm for nonconvex optimization

SGD and Hogwild! Convergence Without the Bounded Gradients Assumption

A state-space mixed membership blockmodel for dynamic network tomography

Tile2Vec: Unsupervised representation learning for spatially distributed data

Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget

Adaptive Machine Unlearning

Apprenticeship Learning using Inverse Reinforcement Learning and Gradient Methods

Relative Density-Ratio Estimation for Robust Distribution Comparison

Branch and Bound for Piecewise Linear Neural Network Verification

Orthogonal Random Features

Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation

Exact and Stable Covariance Estimation from Quadratic Sampling via Convex Programming

Spectral Graph Convolutions for Population-based Disease Prediction

Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations

Deep Embedded Multi-view Clustering with Collaborative Training

Topology and Geometry of Half-Rectified Network Optimization

Degenerate Feedback Loops in Recommender Systems

The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?

Generative replay with feedback connections as a general strategy for continual learning

CXPlain: Causal Explanations for Model Interpretation under Uncertainty

giotto-tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration

TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency

Controlling Fairness and Bias in Dynamic Learning-to-Rank

Lasso Screening Rules via Dual Polytope Projection

Measuring Sample Quality with Stein's Method

Timer: Generative Pre-trained Transformers Are Large Time Series Models

Invariant Representations without Adversarial Training

Perturbed Iterate Analysis for Asynchronous Stochastic Optimization

On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products

Decentralized Collaborative Learning of Personalized Models over Networks

Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction

RKT : Relation-Aware Self-Attention for Knowledge Tracing

Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision

Unsupervised Domain Adaptation through Self-Supervision

Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance

On the Fairness of Disentangled Representations

A Survey of Reinforcement Learning Algorithms for Dynamically Varying Environments

Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multi-Layer Calorimeters

Learning Granger Causality for Hawkes Processes

Policy Learning for Fairness in Ranking

Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning

Non-asymptotic Identification of LTI Systems from a Single Trajectory

Imitation Learning via Off-Policy Distribution Matching

On Iterative Hard Thresholding Methods for High-dimensional M-Estimation

Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and Simplicity

A Close Look at Deep Learning with Small Data

Unifying Human and Statistical Evaluation for Natural Language Generation

Data Valuation using Reinforcement Learning

Making deep neural networks right for the right scientific reasons by interacting with their explanations

Learning image representations tied to ego-motion

Deep Reinforcement Learning for Swarm Systems

Multi-output Bus Travel Time Prediction with Convolutional LSTM Neural Network