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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3,301 to 3,360 of 6,780

Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
Sushravya Raghunath, Alvaro E. Ulloa Cerna, Linyuan Jing +12
q-bio.QMcs.LGstat.MLarXiv:1904.07032v32019
Fast Supervised Discrete Hashing
Jie Gui, Tongliang Liu, Zhenan Sun +2
cs.LGstat.MLarXiv:1904.03556v12019
A Deep Reinforcement Learning Chatbot
Iulian V. Serban, Chinnadhurai Sankar, Mathieu Germain +15
cs.CLcs.AIcs.LGarXiv:1709.02349v22017
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Weizhi Ma, Min Zhang, Yue Cao +6
cs.IRcs.AIcs.LGarXiv:1903.03714v12019
On Identifying Significant Edges in Graphical Models of Molecular Networks
Marco Scutari, Radhakrishnan Nagarajan
stat.MLstat.MEarXiv:1104.0896v52011
MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification
Chang Wei Tan, Angus Dempster, Christoph Bergmeir +1
cs.LGstat.MLarXiv:2102.00457v42021
Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via Thresholded Wirtinger Flow
T. Tony Cai, Xiaodong Li, Zongming Ma
math.STcs.ITmath.NAarXiv:1506.03382v12015
Toward Optimal Feature Selection in Naive Bayes for Text Categorization
Bo Tang, Steven Kay, Haibo He
stat.MLcs.CLcs.IRarXiv:1602.02850v12016
Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning
Georgios Papoudakis, Filippos Christianos, Arrasy Rahman +1
cs.LGcs.AIcs.MAarXiv:1906.04737v12019
Deep Learning for Detecting Building Defects Using Convolutional Neural Networks
Husein Perez, Joseph H. M. Tah, Amir Mosavi
cs.CVcs.AIcs.LGarXiv:1908.04392v12019
Description and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
Yuma Koizumi, Yohei Kawaguchi, Keisuke Imoto +8
eess.AScs.LGcs.SDarXiv:2006.05822v22020
Sparse graphs using exchangeable random measures
François Caron, Emily B. Fox
stat.MEcs.SImath.STarXiv:1401.1137v32014
Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space
Jiechao Xiong, Qing Wang, Zhuoran Yang +7
cs.LGcs.AIstat.MLarXiv:1810.06394v12018
Regularization via Mass Transportation
Soroosh Shafieezadeh-Abadeh, Daniel Kuhn, Peyman Mohajerin Esfahani
math.OCcs.LGstat.MLarXiv:1710.10016v32017
Achieving Optimal Misclassification Proportion in Stochastic Block Model
Chao Gao, Zongming Ma, Anderson Y. Zhang +1
math.STcs.SIstat.MEarXiv:1505.03772v52015
Frequency Bias in Neural Networks for Input of Non-Uniform Density
Ronen Basri, Meirav Galun, Amnon Geifman +3
cs.LGstat.MLarXiv:2003.04560v12020
Provable approximation properties for deep neural networks
Uri Shaham, Alexander Cloninger, Ronald R. Coifman
stat.MLcs.LGcs.NEarXiv:1509.07385v32015
Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery
Samuel Kim, Peter Y. Lu, Srijon Mukherjee +4
cs.LGcs.NEphysics.data-anarXiv:1912.04825v22019
Variational Inference in Nonconjugate Models
Chong Wang, David M. Blei
stat.MLarXiv:1209.4360v42012
Dynamic Weights in Multi-Objective Deep Reinforcement Learning
Axel Abels, Diederik M. Roijers, Tom Lenaerts +2
cs.LGcs.AIstat.MLarXiv:1809.07803v22018
Learning Memory Access Patterns
Milad Hashemi, Kevin Swersky, Jamie A. Smith +5
cs.LGstat.MLarXiv:1803.02329v12018
Federated Visual Classification with Real-World Data Distribution
Tzu-Ming Harry Hsu, Hang Qi, Matthew Brown
cs.LGcs.CVstat.MLarXiv:2003.08082v32020
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
Sharan Vaswani, Aaron Mishkin, Issam Laradji +3
cs.LGmath.OCstat.MLarXiv:1905.09997v52019
Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identification
Shaoxing Mo, Nicholas Zabaras, Xiaoqing Shi +1
stat.MLcs.LGarXiv:1812.09444v12018
On the Iteration Complexity of Hypergradient Computation
Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil +1
stat.MLcs.LGarXiv:2006.16218v22020
A Living Review of Machine Learning for Particle Physics
Matthew Feickert, Benjamin Nachman
hep-phcs.LGhep-exarXiv:2102.02770v12021
Randomized Smoothing of All Shapes and Sizes
Greg Yang, Tony Duan, J. Edward Hu +3
cs.LGcs.CVcs.NEarXiv:2002.08118v52020
Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data
T. Tony Cai, Rong Ma
stat.MLcs.LGmath.STarXiv:2105.07536v42021
Cosine Normalization: Using Cosine Similarity Instead of Dot Product in Neural Networks
Chunjie Luo, Jianfeng Zhan, Lei Wang +1
cs.LGcs.AIstat.MLarXiv:1702.05870v52017
Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel
Stanislav Fort, Gintare Karolina Dziugaite, Mansheej Paul +3
cs.LGstat.MLarXiv:2010.15110v12020
Understanding Membership Inferences on Well-Generalized Learning Models
Yunhui Long, Vincent Bindschaedler, Lei Wang +5
cs.CRcs.LGstat.MLarXiv:1802.04889v12018
Nested Hierarchical Dirichlet Processes
John Paisley, Chong Wang, David M. Blei +1
stat.MLcs.LGarXiv:1210.6738v42012
Tensor Canonical Correlation Analysis for Multi-view Dimension Reduction
Yong Luo, Dacheng Tao, Yonggang Wen +2
stat.MLcs.CVcs.LGarXiv:1502.02330v12015
A note on the triangle inequality for the Jaccard distance
Sven Kosub
cs.DMcs.IRcs.LGarXiv:1612.02696v12016
DIVA: Domain Invariant Variational Autoencoders
Maximilian Ilse, Jakub M. Tomczak, Christos Louizos +1
stat.MLcs.LGarXiv:1905.10427v22019
On the Origin of Implicit Regularization in Stochastic Gradient Descent
Samuel L. Smith, Benoit Dherin, David G. T. Barrett +1
cs.LGstat.MLarXiv:2101.12176v12021
Adversarial Filters of Dataset Biases
Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula +4
cs.LGcs.AIcs.CLarXiv:2002.04108v32020
Deep Gaussian Processes for Regression using Approximate Expectation Propagation
Thang D. Bui, Daniel Hernández-Lobato, Yingzhen Li +2
stat.MLcs.LGarXiv:1602.04133v12016
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees
Yuping Luo, Huazhe Xu, Yuanzhi Li +3
cs.LGcs.AIstat.MLarXiv:1807.03858v52018
The Unreasonable Ineffectiveness of the Deeper Layers
Andrey Gromov, Kushal Tirumala, Hassan Shapourian +2
cs.CLcs.LGstat.MLarXiv:2403.17887v22024
Autoregressive Diffusion Models
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings +3
cs.LGstat.MLarXiv:2110.02037v22021
Bayesian stochastic blockmodeling
Tiago P. Peixoto
stat.MLcond-mat.stat-mechphysics.data-anarXiv:1705.10225v92017
Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising
Junwei Pan, Jian Xu, Alfonso Lobos Ruiz +4
cs.LGstat.MLarXiv:1806.03514v22018
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments
Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas +4
cs.LGcs.CRstat.MLarXiv:2004.05703v12020
A Simple Convergence Proof of Adam and Adagrad
Alexandre Défossez, Léon Bottou, Francis Bach +1
stat.MLcs.LGarXiv:2003.02395v32020
Adaptive Online Learning in Dynamic Environments
Lijun Zhang, Shiyin Lu, Zhi-Hua Zhou
cs.LGstat.MLarXiv:1810.10815v12018
Application of Convolutional Neural Network to Predict Airfoil Lift Coefficient
Yao Zhang, Woong-Je Sung, Dimitri Mavris
stat.MLcs.LGarXiv:1712.10082v22017
Simple Black-Box Adversarial Perturbations for Deep Networks
Nina Narodytska, Shiva Prasad Kasiviswanathan
cs.LGcs.CRstat.MLarXiv:1612.06299v12016
Parallel training of DNNs with Natural Gradient and Parameter Averaging
Daniel Povey, Xiaohui Zhang, Sanjeev Khudanpur
cs.NEcs.LGstat.MLarXiv:1410.7455v82014
Language as an Abstraction for Hierarchical Deep Reinforcement Learning
Yiding Jiang, Shixiang Gu, Kevin Murphy +1
cs.LGcs.AIcs.CLarXiv:1906.07343v22019
Understanding Gradient Clipping in Private SGD: A Geometric Perspective
Xiangyi Chen, Zhiwei Steven Wu, Mingyi Hong
cs.LGcs.CRmath.OCarXiv:2006.15429v22020
High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks
Krzysztof J. Geras, Stacey Wolfson, Yiqiu Shen +7
cs.CVcs.LGstat.MLarXiv:1703.07047v32017
Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection
Julie Nutini, Mark Schmidt, Issam H. Laradji +2
math.OCcs.LGstat.COarXiv:1506.00552v22015
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization
Paras Jain, Ajay Jain, Aniruddha Nrusimha +5
cs.LGcs.CVcs.DCarXiv:1910.02653v32019
On Feature Decorrelation in Self-Supervised Learning
Tianyu Hua, Wenxiao Wang, Zihui Xue +3
cs.LGcs.AIcs.CVarXiv:2105.00470v22021
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

Machine Learning (stat)

Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data

Fast Supervised Discrete Hashing

A Deep Reinforcement Learning Chatbot

Jointly Learning Explainable Rules for Recommendation with Knowledge Graph

On Identifying Significant Edges in Graphical Models of Molecular Networks

MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification

Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via Thresholded Wirtinger Flow

Toward Optimal Feature Selection in Naive Bayes for Text Categorization

Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning

Deep Learning for Detecting Building Defects Using Convolutional Neural Networks

Description and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

Sparse graphs using exchangeable random measures

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space

Regularization via Mass Transportation

Achieving Optimal Misclassification Proportion in Stochastic Block Model

Frequency Bias in Neural Networks for Input of Non-Uniform Density

Provable approximation properties for deep neural networks

Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery

Variational Inference in Nonconjugate Models

Dynamic Weights in Multi-Objective Deep Reinforcement Learning

Learning Memory Access Patterns

Federated Visual Classification with Real-World Data Distribution

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates

Deep autoregressive neural networks for high-dimensional inverse problems in groundwater contaminant source identification

On the Iteration Complexity of Hypergradient Computation

A Living Review of Machine Learning for Particle Physics

Randomized Smoothing of All Shapes and Sizes

Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data

Cosine Normalization: Using Cosine Similarity Instead of Dot Product in Neural Networks

Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel

Understanding Membership Inferences on Well-Generalized Learning Models

Nested Hierarchical Dirichlet Processes

Tensor Canonical Correlation Analysis for Multi-view Dimension Reduction

A note on the triangle inequality for the Jaccard distance

DIVA: Domain Invariant Variational Autoencoders

On the Origin of Implicit Regularization in Stochastic Gradient Descent

Adversarial Filters of Dataset Biases

Deep Gaussian Processes for Regression using Approximate Expectation Propagation

Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees

The Unreasonable Ineffectiveness of the Deeper Layers

Autoregressive Diffusion Models

Bayesian stochastic blockmodeling

Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising

DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments

A Simple Convergence Proof of Adam and Adagrad

Adaptive Online Learning in Dynamic Environments

Application of Convolutional Neural Network to Predict Airfoil Lift Coefficient

Simple Black-Box Adversarial Perturbations for Deep Networks

Parallel training of DNNs with Natural Gradient and Parameter Averaging

Language as an Abstraction for Hierarchical Deep Reinforcement Learning

Understanding Gradient Clipping in Private SGD: A Geometric Perspective

High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks

Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection

Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization

On Feature Decorrelation in Self-Supervised Learning

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