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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721 to 780 of 6,786

Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
Gintare Karolina Dziugaite, Daniel M. Roy
stat.MLcs.LGarXiv:1712.09376v32017
On the Computational Complexity of High-Dimensional Bayesian Variable Selection
Yun Yang, Martin J. Wainwright, Michael I. Jordan
math.STcs.LGstat.COarXiv:1505.07925v12015
Nonparametric Bayesian sparse factor models with application to gene expression modeling
David Knowles, Zoubin Ghahramani
stat.APcs.AIstat.MLarXiv:1011.6293v22010
Robust Subspace Clustering via Thresholding
Reinhard Heckel, Helmut Bölcskei
stat.MLcs.ITcs.LGarXiv:1307.4891v42013
Rates of Convergence for Nearest Neighbor Classification
Kamalika Chaudhuri, Sanjoy Dasgupta
cs.LGmath.STstat.MLarXiv:1407.0067v22014
A Disease Diagnosis and Treatment Recommendation System Based on Big Data Mining and Cloud Computing
Jianguo Chen, Kenli Li, Huigui Rong +3
cs.LGstat.MLarXiv:1810.07762v12018
Accurate Genomic Prediction Of Human Height
Louis Lello, Steven G. Avery, Laurent Tellier +3
q-bio.GNcs.LGq-bio.QMarXiv:1709.06489v12017
Improving Chemical Autoencoder Latent Space and Molecular De novo Generation Diversity with Heteroencoders
Esben Jannik Bjerrum, Boris Sattarov
cs.LGstat.MLarXiv:1806.09300v22018
Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods
Min Lu, Saad Sadiq, Daniel J. Feaster +1
stat.MLarXiv:1701.05306v22017
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey
Samuel Henrique Silva, Peyman Najafirad
cs.LGcs.AIstat.MLarXiv:2007.00753v22020
Data-driven polynomial chaos expansion for machine learning regression
E. Torre, S. Marelli, P. Embrechts +1
stat.MLcs.LGstat.COarXiv:1808.03216v22018
Bias and Generalization in Deep Generative Models: An Empirical Study
Shengjia Zhao, Hongyu Ren, Arianna Yuan +3
cs.LGstat.MLarXiv:1811.03259v12018
Solving for high dimensional committor functions using artificial neural networks
Yuehaw Khoo, Jianfeng Lu, Lexing Ying
cs.LGmath.NAstat.MLarXiv:1802.10275v12018
Collaborative Machine Learning with Incentive-Aware Model Rewards
Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan +1
cs.LGcs.GTcs.MAarXiv:2010.12797v12020
Second-Order Optimization for Non-Convex Machine Learning: An Empirical Study
Peng Xu, Farbod Roosta-Khorasani, Michael W. Mahoney
math.OCcs.LGmath.NAarXiv:1708.07827v22017
Intention-aware Long Horizon Trajectory Prediction of Surrounding Vehicles using Dual LSTM Networks
Long Xin, Pin Wang, Ching-Yao Chan +3
cs.LGcs.ROstat.MLarXiv:1906.02815v12019
Fast Multi-language LSTM-based Online Handwriting Recognition
Victor Carbune, Pedro Gonnet, Thomas Deselaers +7
cs.CLcs.LGstat.MLarXiv:1902.10525v22019
Learning Neural PDE Solvers with Convergence Guarantees
Jun-Ting Hsieh, Shengjia Zhao, Stephan Eismann +2
math.NAstat.COstat.MLarXiv:1906.01200v12019
MahNMF: Manhattan Non-negative Matrix Factorization
Naiyang Guan, Dacheng Tao, Zhigang Luo +1
stat.MLcs.LGmath.NAarXiv:1207.3438v12012
Eigenvalue and Generalized Eigenvalue Problems: Tutorial
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
stat.MLcs.LGarXiv:1903.11240v32019
Analogies Explained: Towards Understanding Word Embeddings
Carl Allen, Timothy Hospedales
cs.CLcs.LGstat.MLarXiv:1901.09813v22019
Pavement Image Datasets: A New Benchmark Dataset to Classify and Densify Pavement Distresses
Hamed Majidifard, Peng Jin, Yaw Adu-Gyamfi +1
cs.CVcs.LGstat.MLarXiv:1910.11123v22019
Weisfeiler and Leman go Machine Learning: The Story so far
Christopher Morris, Yaron Lipman, Haggai Maron +5
cs.LGcs.DScs.NEarXiv:2112.09992v42021
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary
Byeongho Heo, Minsik Lee, Sangdoo Yun +1
cs.LGcs.CVstat.MLarXiv:1805.05532v42018
Mitigating backdoor attacks in LSTM-based Text Classification Systems by Backdoor Keyword Identification
Chuanshuai Chen, Jiazhu Dai
cs.CRcs.LGstat.MLarXiv:2007.12070v32020
Hierarchical interpretations for neural network predictions
Chandan Singh, W. James Murdoch, Bin Yu
cs.LGcs.AIcs.CLarXiv:1806.05337v22018
Community Detection and Classification in Hierarchical Stochastic Blockmodels
Vince Lyzinski, Minh Tang, Avanti Athreya +2
stat.MLstat.AParXiv:1503.02115v52015
Deep Imitative Models for Flexible Inference, Planning, and Control
Nicholas Rhinehart, Rowan McAllister, Sergey Levine
cs.LGcs.AIcs.CVarXiv:1810.06544v42018
FreezeOut: Accelerate Training by Progressively Freezing Layers
Andrew Brock, Theodore Lim, J. M. Ritchie +1
stat.MLcs.LGarXiv:1706.04983v22017
On Learning Invariant Representation for Domain Adaptation
Han Zhao, Remi Tachet des Combes, Kun Zhang +1
cs.LGcs.AIstat.MLarXiv:1901.09453v22019
Thompson Sampling for 1-Dimensional Exponential Family Bandits
Nathaniel Korda, Emilie Kaufmann, Remi Munos
stat.MLarXiv:1307.3400v12013
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability
Alex Damian, Eshaan Nichani, Jason D. Lee
cs.LGcs.ITmath.OCarXiv:2209.15594v22022
Contrastive Learning for Weakly Supervised Phrase Grounding
Tanmay Gupta, Arash Vahdat, Gal Chechik +3
cs.CVcs.CLcs.LGarXiv:2006.09920v32020
Accelerating Deep Learning by Focusing on the Biggest Losers
Angela H. Jiang, Daniel L. -K. Wong, Giulio Zhou +8
cs.LGstat.MLarXiv:1910.00762v12019
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
Chao Ma, Sebastian Tschiatschek, Konstantina Palla +3
cs.LGstat.MLarXiv:1809.11142v42018
Accelerating Stochastic Composition Optimization
Mengdi Wang, Ji Liu, Ethan X. Fang
math.OCstat.MLarXiv:1607.07329v12016
A review of predictive uncertainty estimation with machine learning
Hristos Tyralis, Georgia Papacharalampous
stat.MLcs.LGmath.STarXiv:2209.08307v22022
Adversarially Robust Generalization Just Requires More Unlabeled Data
Runtian Zhai, Tianle Cai, Di He +4
cs.LGstat.MLarXiv:1906.00555v22019
Visualizing Data using GTSNE
Songting Shi
cs.LGcs.HCmath.OCarXiv:2108.01301v12021
Transformers as In-Context Samplers: From Closed-Form Diffusion to Estimation-Free Sampling
Arman Adibi, Alireza Jafari, Mohammad Ghavamzadeh +1
cs.LGcs.AIstat.AParXiv:2609.08981v12026
Fast convolutional neural networks on FPGAs with hls4ml
Thea Aarrestad, Vladimir Loncar, Nicolò Ghielmetti +17
cs.LGcs.CVhep-exarXiv:2101.05108v22021
Detecting weak and strong Islamophobic hate speech on social media
Bertie Vidgen, Taha Yasseri
cs.CLcs.LGstat.MLarXiv:1812.10400v12018
Neural Network Approximation: Three Hidden Layers Are Enough
Zuowei Shen, Haizhao Yang, Shijun Zhang
cs.LGcs.NEstat.MLarXiv:2010.14075v42020
A Bayesian approach to constrained single- and multi-objective optimization
Paul Feliot, Julien Bect, Emmanuel Vazquez
stat.COstat.MLarXiv:1510.00503v32015
Sample Efficient Adaptive Text-to-Speech
Yutian Chen, Yannis Assael, Brendan Shillingford +11
cs.LGcs.SDstat.MLarXiv:1809.10460v32018
The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint
Stephen Tu, Benjamin Recht
cs.LGmath.OCstat.MLarXiv:1812.03565v22018
A Bayesian machine scientist to aid in the solution of challenging scientific problems
Roger Guimera, Ignasi Reichardt, Antoni Aguilar-Mogas +4
cs.LGphysics.data-anstat.MLarXiv:2004.12157v12020
Supervised, semi-supervised and unsupervised inference of gene regulatory networks
Stefan R. Maetschke, Piyush B. Madhamshettiwar, Melissa J. Davis +1
q-bio.MNq-bio.QMstat.MLarXiv:1301.1083v12013
Low-rank Kernel Learning for Graph-based Clustering
Zhao Kang, Liangjian Wen, Wenyu Chen +1
cs.LGcs.CVstat.MLarXiv:1903.05962v12019
Clustering with Multi-Layer Graphs: A Spectral Perspective
Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst +1
cs.LGcs.CVcs.SIarXiv:1106.2233v12011
Algorithms, Initializations, and Convergence for the Nonnegative Matrix Factorization
Amy N. Langville, Carl D. Meyer, Russell Albright +2
math.NAcs.LGstat.MLarXiv:1407.7299v12014
Learning Montezuma's Revenge from a Single Demonstration
Tim Salimans, Richard Chen
cs.LGcs.AIcs.NEarXiv:1812.03381v12018
Deep Generative Adversarial Networks for Compressed Sensing Automates MRI
Morteza Mardani, Enhao Gong, Joseph Y. Cheng +8
cs.CVcs.LGstat.MLarXiv:1706.00051v12017
DeepMoD: Deep learning for Model Discovery in noisy data
Gert-Jan Both, Subham Choudhury, Pierre Sens +1
physics.comp-phq-bio.QMstat.MLarXiv:1904.09406v32019
A Model of Double Descent for High-dimensional Binary Linear Classification
Zeyu Deng, Abla Kammoun, Christos Thrampoulidis
stat.MLcs.LGeess.SParXiv:1911.05822v22019
Infinite Feature Selection: A Graph-based Feature Filtering Approach
Giorgio Roffo, Simone Melzi, Umberto Castellani +2
cs.CVcs.LGstat.MLarXiv:2006.08184v12020
Sudo rm -rf: Efficient Networks for Universal Audio Source Separation
Efthymios Tzinis, Zhepei Wang, Paris Smaragdis
eess.AScs.CLcs.LGarXiv:2007.06833v12020
A Unified Deep Neural Network for Speaker and Language Recognition
Fred Richardson, Douglas Reynolds, Najim Dehak
cs.CLcs.CVcs.LGarXiv:1504.00923v12015
Variance Reduced Local SGD with Lower Communication Complexity
Xianfeng Liang, Shuheng Shen, Jingchang Liu +3
cs.LGcs.DCmath.OCarXiv:1912.12844v12019
CASTER: Predicting Drug Interactions with Chemical Substructure Representation
Kexin Huang, Cao Xiao, Trong Nghia Hoang +2
cs.LGq-bio.QMstat.MLarXiv:1911.06446v22019

Machine Learning (stat)

Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors

On the Computational Complexity of High-Dimensional Bayesian Variable Selection

Nonparametric Bayesian sparse factor models with application to gene expression modeling

Robust Subspace Clustering via Thresholding

Rates of Convergence for Nearest Neighbor Classification

A Disease Diagnosis and Treatment Recommendation System Based on Big Data Mining and Cloud Computing

Accurate Genomic Prediction Of Human Height

Improving Chemical Autoencoder Latent Space and Molecular De novo Generation Diversity with Heteroencoders

Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods

Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey

Data-driven polynomial chaos expansion for machine learning regression

Bias and Generalization in Deep Generative Models: An Empirical Study

Solving for high dimensional committor functions using artificial neural networks

Collaborative Machine Learning with Incentive-Aware Model Rewards

Second-Order Optimization for Non-Convex Machine Learning: An Empirical Study

Intention-aware Long Horizon Trajectory Prediction of Surrounding Vehicles using Dual LSTM Networks

Fast Multi-language LSTM-based Online Handwriting Recognition

Learning Neural PDE Solvers with Convergence Guarantees

MahNMF: Manhattan Non-negative Matrix Factorization

Eigenvalue and Generalized Eigenvalue Problems: Tutorial

Analogies Explained: Towards Understanding Word Embeddings

Pavement Image Datasets: A New Benchmark Dataset to Classify and Densify Pavement Distresses

Weisfeiler and Leman go Machine Learning: The Story so far

Knowledge Distillation with Adversarial Samples Supporting Decision Boundary

Mitigating backdoor attacks in LSTM-based Text Classification Systems by Backdoor Keyword Identification

Hierarchical interpretations for neural network predictions

Community Detection and Classification in Hierarchical Stochastic Blockmodels

Deep Imitative Models for Flexible Inference, Planning, and Control

FreezeOut: Accelerate Training by Progressively Freezing Layers

On Learning Invariant Representation for Domain Adaptation

Thompson Sampling for 1-Dimensional Exponential Family Bandits

Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability

Contrastive Learning for Weakly Supervised Phrase Grounding

Accelerating Deep Learning by Focusing on the Biggest Losers

EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE

Accelerating Stochastic Composition Optimization

A review of predictive uncertainty estimation with machine learning

Adversarially Robust Generalization Just Requires More Unlabeled Data

Visualizing Data using GTSNE

Transformers as In-Context Samplers: From Closed-Form Diffusion to Estimation-Free Sampling

Fast convolutional neural networks on FPGAs with hls4ml

Detecting weak and strong Islamophobic hate speech on social media

Neural Network Approximation: Three Hidden Layers Are Enough

A Bayesian approach to constrained single- and multi-objective optimization

Sample Efficient Adaptive Text-to-Speech

The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint

A Bayesian machine scientist to aid in the solution of challenging scientific problems

Supervised, semi-supervised and unsupervised inference of gene regulatory networks

Low-rank Kernel Learning for Graph-based Clustering

Clustering with Multi-Layer Graphs: A Spectral Perspective

Algorithms, Initializations, and Convergence for the Nonnegative Matrix Factorization

Learning Montezuma's Revenge from a Single Demonstration

Deep Generative Adversarial Networks for Compressed Sensing Automates MRI

DeepMoD: Deep learning for Model Discovery in noisy data

A Model of Double Descent for High-dimensional Binary Linear Classification

Infinite Feature Selection: A Graph-based Feature Filtering Approach

Sudo rm -rf: Efficient Networks for Universal Audio Source Separation

A Unified Deep Neural Network for Speaker and Language Recognition

Variance Reduced Local SGD with Lower Communication Complexity

CASTER: Predicting Drug Interactions with Chemical Substructure Representation