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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2,881 to 2,940 of 6,773

A Unified Lottery Ticket Hypothesis for Graph Neural Networks
Tianlong Chen, Yongduo Sui, Xuxi Chen +2
cs.LGcs.AIstat.MLarXiv:2102.06790v22021
Tempered Sigmoid Activations for Deep Learning with Differential Privacy
Nicolas Papernot, Abhradeep Thakurta, Shuang Song +2
stat.MLcs.CRcs.LGarXiv:2007.14191v12020
A Deep and Tractable Density Estimator
Benigno Uria, Iain Murray, Hugo Larochelle
stat.MLcs.LGarXiv:1310.1757v22013
Predictive Multiplicity in Classification
Charles T. Marx, Flavio du Pin Calmon, Berk Ustun
cs.LGcs.CYstat.MLarXiv:1909.06677v42019
Set Functions for Time Series
Max Horn, Michael Moor, Christian Bock +2
cs.LGstat.MLarXiv:1909.12064v32019
Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models
Jiawei Zhang, Yang Wang, Piero Molino +2
cs.LGcs.HCstat.MLarXiv:1808.00196v12018
Machine learning in resting-state fMRI analysis
Meenakshi Khosla, Keith Jamison, Gia H. Ngo +2
cs.LGcs.CVq-bio.QMarXiv:1812.11477v12018
Meta-Learning with Warped Gradient Descent
Sebastian Flennerhag, Andrei A. Rusu, Razvan Pascanu +3
cs.LGcs.NEstat.MLarXiv:1909.00025v22019
Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive Models
Jianqing Fan, Yang Feng, Rui Song
stat.MEmath.STstat.COarXiv:0912.2695v22009
Hierarchical Imitation and Reinforcement Learning
Hoang M. Le, Nan Jiang, Alekh Agarwal +3
cs.LGcs.AIstat.MLarXiv:1803.00590v22018
Modern Bayesian Experimental Design
Tom Rainforth, Adam Foster, Desi R Ivanova +1
stat.MLcs.AIcs.LGarXiv:2302.14545v22023
Iterative Hessian sketch: Fast and accurate solution approximation for constrained least-squares
Mert Pilanci, Martin J. Wainwright
math.OCcs.ITcs.LGarXiv:1411.0347v12014
Overcoming critical slowing down in frustrated spin systems by learned multiscale sampling
Gabriele Bandini, Giulio Biroli, Patrick Charbonneau +1
cond-mat.stat-mechstat.MLarXiv:2608.31114v12026
Off-Policy Multi-Agent Decomposed Policy Gradients
Yihan Wang, Beining Han, Tonghan Wang +2
cs.LGcs.MAstat.MLarXiv:2007.12322v22020
Summaries:한국어
FALKON: An Optimal Large Scale Kernel Method
Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco
stat.MLcs.LGarXiv:1705.10958v32017
Transfer learning based multi-fidelity physics informed deep neural network
Souvik Chakraborty
cs.LGphysics.comp-phstat.MLarXiv:2005.10614v22020
Greedy Layerwise Learning Can Scale to ImageNet
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
cs.LGstat.MLarXiv:1812.11446v32018
Approximate Kernel-based Conditional Independence Tests for Fast Non-Parametric Causal Discovery
Eric V. Strobl, Kun Zhang, Shyam Visweswaran
stat.MEstat.MLarXiv:1702.03877v22017
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary
Huan Zhang, Hongge Chen, Duane Boning +1
cs.LGcs.AIstat.MLarXiv:2101.08452v12021
Quantum Variational Autoencoder
Amir Khoshaman, Walter Vinci, Brandon Denis +3
quant-phcs.LGstat.MLarXiv:1802.05779v22018
Latent Dirichlet Allocation (LDA) for Topic Modeling of the CFPB Consumer Complaints
Kaveh Bastani, Hamed Namavari, Jeffry Shaffer
cs.IRcs.LGstat.MLarXiv:1807.07468v12018
Multimodal Language Analysis with Recurrent Multistage Fusion
Paul Pu Liang, Ziyin Liu, Amir Zadeh +1
cs.LGcs.AIcs.CLarXiv:1808.03920v12018
3D-PRNN: Generating Shape Primitives with Recurrent Neural Networks
Chuhang Zou, Ersin Yumer, Jimei Yang +2
cs.CVcs.AIcs.LGarXiv:1708.01648v12017
Detailed comparison of communication efficiency of split learning and federated learning
Abhishek Singh, Praneeth Vepakomma, Otkrist Gupta +1
cs.LGcs.DCstat.MLarXiv:1909.09145v12019
Batch Normalized Recurrent Neural Networks
César Laurent, Gabriel Pereyra, Philémon Brakel +2
stat.MLcs.LGcs.NEarXiv:1510.01378v12015
Learning from Dialogue after Deployment: Feed Yourself, Chatbot!
Braden Hancock, Antoine Bordes, Pierre-Emmanuel Mazaré +1
cs.CLcs.AIcs.HCarXiv:1901.05415v42019
Editable Neural Networks
Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitriy Pyrkin +2
cs.LGstat.MLarXiv:2004.00345v22020
On Formalizing Fairness in Prediction with Machine Learning
Pratik Gajane, Mykola Pechenizkiy
cs.LGcs.AIstat.MLarXiv:1710.03184v32017
Offline Handwritten Signature Verification - Literature Review
Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
cs.CVstat.MLarXiv:1507.07909v42015
Exploratory Combinatorial Optimization with Reinforcement Learning
Thomas D. Barrett, William R. Clements, Jakob N. Foerster +1
cs.LGcs.AIstat.MLarXiv:1909.04063v22019
Predicting the Generalization Gap in Deep Networks with Margin Distributions
Yiding Jiang, Dilip Krishnan, Hossein Mobahi +1
stat.MLcs.LGarXiv:1810.00113v22018
Learning with Biased Complementary Labels
Xiyu Yu, Tongliang Liu, Mingming Gong +1
stat.MLcs.LGarXiv:1711.09535v32017
Theoretical Analysis of Domain Adaptation with Optimal Transport
Ievgen Redko, Amaury Habrard, Marc Sebban
stat.MLcs.LGarXiv:1610.04420v42016
Self-supervised representation learning from 12-lead ECG data
Temesgen Mehari, Nils Strodthoff
eess.SPcs.LGstat.MLarXiv:2103.12676v22021
Relational recurrent neural networks
Adam Santoro, Ryan Faulkner, David Raposo +7
cs.LGstat.MLarXiv:1806.01822v22018
Benign overfitting in ridge regression
A. Tsigler, P. L. Bartlett
math.STstat.MLarXiv:2009.14286v22020
Metric Learning with Adaptive Density Discrimination
Oren Rippel, Manohar Paluri, Piotr Dollar +1
stat.MLcs.LGarXiv:1511.05939v22015
Equivariant Subgraph Aggregation Networks
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim +5
cs.LGstat.MLarXiv:2110.02910v32021
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators
Dingfan Chen, Tribhuvanesh Orekondy, Mario Fritz
cs.LGcs.CRstat.MLarXiv:2006.08265v22020
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Matthias Hein, Thomas Bühler
cs.LGmath.OCstat.MLarXiv:1012.0774v12010
Conditional Generative Adversarial Networks for Speech Enhancement and Noise-Robust Speaker Verification
Daniel Michelsanti, Zheng-Hua Tan
eess.AScs.LGcs.SDarXiv:1709.01703v22017
AI-based Modeling and Data-driven Evaluation for Smart Manufacturing Processes
Mohammadhossein Ghahramani, Yan Qiao, MengChu Zhou +2
cs.LGstat.MLarXiv:2008.12987v12020
Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound
Oren Solomon, Regev Cohen, Yi Zhang +5
cs.LGeess.SPstat.MLarXiv:1811.08252v12018
DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentation
Nina Varney, Vijayan K. Asari, Quinn Graehling
cs.CVcs.LGstat.MLarXiv:2004.11985v12020
Intensity-Free Learning of Temporal Point Processes
Oleksandr Shchur, Marin Biloš, Stephan Günnemann
cs.LGstat.MLarXiv:1909.12127v22019
Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform
Zhenyu Zhao, Radhika Anand, Mallory Wang
stat.MLcs.LGarXiv:1908.05376v12019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward
Adnan Qayyum, Muhammad Usama, Junaid Qadir +1
cs.LGcs.CRstat.MLarXiv:1905.12762v12019
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks
Jen-Cheng Hou, Syu-Siang Wang, Ying-Hui Lai +3
cs.SDcs.MMeess.ASarXiv:1709.00944v52017
Diversity-Sensitive Conditional Generative Adversarial Networks
Dingdong Yang, Seunghoon Hong, Yunseok Jang +2
cs.LGstat.MLarXiv:1901.09024v12019
What Do Compressed Deep Neural Networks Forget?
Sara Hooker, Aaron Courville, Gregory Clark +2
cs.LGcs.AIcs.CVarXiv:1911.05248v32019
A General Algorithm for Deciding Transportability of Experimental Results
Elias Bareinboim, Judea Pearl
cs.AIstat.MEstat.MLarXiv:1312.7485v12013
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Michael Roberts, Derek Driggs, Matthew Thorpe +13
cs.LGcs.CVeess.IVarXiv:2008.06388v42020
Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit
Chong You, Daniel P. Robinson, Rene Vidal
cs.CVcs.LGstat.MLarXiv:1507.01238v32015
Between-class Learning for Image Classification
Yuji Tokozume, Yoshitaka Ushiku, Tatsuya Harada
cs.LGcs.CVstat.MLarXiv:1711.10284v22017
Explainable artificial intelligence model to predict acute critical illness from electronic health records
Simon Meyer Lauritsen, Mads Kristensen, Mathias Vassard Olsen +5
cs.AIcs.LGstat.AParXiv:1912.01266v12019
Truly Proximal Policy Optimization
Yuhui Wang, Hao He, Chao Wen +1
cs.LGcs.AIstat.MLarXiv:1903.07940v22019
Veridical Data Science
Bin Yu, Karl Kumbier
stat.MLcs.LGarXiv:1901.08152v52019
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Tengfei Ma, Jie Chen, Cao Xiao
cs.LGstat.MLarXiv:1809.02630v22018
Higher-Order Factorization Machines
Mathieu Blondel, Akinori Fujino, Naonori Ueda +1
stat.MLcs.LGarXiv:1607.07195v22016
Deep Learning Approximation for Stochastic Control Problems
Jiequn Han, Weinan E
cs.LGcs.AIcs.NEarXiv:1611.07422v12016

Machine Learning (stat)

A Unified Lottery Ticket Hypothesis for Graph Neural Networks

Tempered Sigmoid Activations for Deep Learning with Differential Privacy

A Deep and Tractable Density Estimator

Predictive Multiplicity in Classification

Set Functions for Time Series

Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models

Machine learning in resting-state fMRI analysis

Meta-Learning with Warped Gradient Descent

Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive Models

Hierarchical Imitation and Reinforcement Learning

Modern Bayesian Experimental Design

Iterative Hessian sketch: Fast and accurate solution approximation for constrained least-squares

Overcoming critical slowing down in frustrated spin systems by learned multiscale sampling

Off-Policy Multi-Agent Decomposed Policy Gradients

FALKON: An Optimal Large Scale Kernel Method

Transfer learning based multi-fidelity physics informed deep neural network

Greedy Layerwise Learning Can Scale to ImageNet

Approximate Kernel-based Conditional Independence Tests for Fast Non-Parametric Causal Discovery

Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Quantum Variational Autoencoder

Latent Dirichlet Allocation (LDA) for Topic Modeling of the CFPB Consumer Complaints

Multimodal Language Analysis with Recurrent Multistage Fusion

3D-PRNN: Generating Shape Primitives with Recurrent Neural Networks

Detailed comparison of communication efficiency of split learning and federated learning

Batch Normalized Recurrent Neural Networks

Learning from Dialogue after Deployment: Feed Yourself, Chatbot!

Editable Neural Networks

On Formalizing Fairness in Prediction with Machine Learning

Offline Handwritten Signature Verification - Literature Review

Exploratory Combinatorial Optimization with Reinforcement Learning

Predicting the Generalization Gap in Deep Networks with Margin Distributions

Learning with Biased Complementary Labels

Theoretical Analysis of Domain Adaptation with Optimal Transport

Self-supervised representation learning from 12-lead ECG data

Relational recurrent neural networks

Benign overfitting in ridge regression

Metric Learning with Adaptive Density Discrimination

Equivariant Subgraph Aggregation Networks

GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators

An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA

Conditional Generative Adversarial Networks for Speech Enhancement and Noise-Robust Speaker Verification

AI-based Modeling and Data-driven Evaluation for Smart Manufacturing Processes

Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound

DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentation

Intensity-Free Learning of Temporal Point Processes

Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform

Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward

Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks

Diversity-Sensitive Conditional Generative Adversarial Networks

What Do Compressed Deep Neural Networks Forget?

A General Algorithm for Deciding Transportability of Experimental Results

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit

Between-class Learning for Image Classification

Explainable artificial intelligence model to predict acute critical illness from electronic health records

Truly Proximal Policy Optimization

Veridical Data Science

Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders

Higher-Order Factorization Machines

Deep Learning Approximation for Stochastic Control Problems