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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4,981 to 5,040 of 6,790

Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices
Tayfun Gokmen, Yurii Vlasov
cs.LGcs.NEstat.MLarXiv:1603.07341v12016
Is Pessimism Provably Efficient for Offline RL?
Ying Jin, Zhuoran Yang, Zhaoran Wang
cs.LGcs.AImath.OCarXiv:2012.15085v32020
Learning to Perform Local Rewriting for Combinatorial Optimization
Xinyun Chen, Yuandong Tian
cs.LGcs.AIstat.MLarXiv:1810.00337v52018
Robust Kernel Density Estimation
JooSeuk Kim, Clayton D. Scott
stat.MLcs.LGstat.MEarXiv:1107.3133v22011
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition
Yao Qin, Nicholas Carlini, Ian Goodfellow +2
eess.AScs.LGcs.SDarXiv:1903.10346v22019
Stacked Bidirectional and Unidirectional LSTM Recurrent Neural Network for Forecasting Network-wide Traffic State with Missing Values
Zhiyong Cui, Ruimin Ke, Ziyuan Pu +1
cs.LGeess.SPstat.MLarXiv:2005.11627v12020
The Frontiers of Fairness in Machine Learning
Alexandra Chouldechova, Aaron Roth
cs.LGcs.DScs.GTarXiv:1810.08810v12018
Deep Kalman Filters
Rahul G. Krishnan, Uri Shalit, David Sontag
stat.MLcs.LGarXiv:1511.05121v22015
Fast and Accurate Recurrent Neural Network Acoustic Models for Speech Recognition
Haşim Sak, Andrew Senior, Kanishka Rao +1
cs.CLcs.LGcs.NEarXiv:1507.06947v12015
A Scalable Bootstrap for Massive Data
Ariel Kleiner, Ameet Talwalkar, Purnamrita Sarkar +1
stat.MEstat.COstat.MLarXiv:1112.5016v22011
Learning in Implicit Generative Models
Shakir Mohamed, Balaji Lakshminarayanan
stat.MLcs.LGstat.COarXiv:1610.03483v42016
Neural networks for post-processing ensemble weather forecasts
Stephan Rasp, Sebastian Lerch
stat.MLcs.LGphysics.ao-pharXiv:1805.09091v12018
Sequential Neural Models with Stochastic Layers
Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet +1
stat.MLcs.LGarXiv:1605.07571v22016
A survey of dimensionality reduction techniques
C. O. S. Sorzano, J. Vargas, A. Pascual Montano
stat.MLcs.LGq-bio.QMarXiv:1403.2877v12014
Towards a Neural Statistician
Harrison Edwards, Amos Storkey
stat.MLcs.LGarXiv:1606.02185v22016
Is feature selection secure against training data poisoning?
Huang Xiao, Battista Biggio, Gavin Brown +3
cs.LGcs.CRcs.GTarXiv:1804.07933v12018
Deep Learning of Vortex Induced Vibrations
Maziar Raissi, Zhicheng Wang, Michael S. Triantafyllou +1
physics.flu-dyncs.CEcs.LGarXiv:1808.08952v12018
Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models
Lasse F. Wolff Anthony, Benjamin Kanding, Raghavendra Selvan
cs.CYcs.LGeess.SParXiv:2007.03051v12020
Adversarial Policies: Attacking Deep Reinforcement Learning
Adam Gleave, Michael Dennis, Cody Wild +3
cs.LGcs.AIcs.CRarXiv:1905.10615v32019
Kernel and Rich Regimes in Overparametrized Models
Blake Woodworth, Suriya Gunasekar, Jason D. Lee +5
cs.LGstat.MLarXiv:2002.09277v32020
Why not to use the Gaussian kernel
Toni Karvonen, Chris J. Oates
stat.MLcs.LGmath.NAarXiv:2608.26974v12026
Soft Weight-Sharing for Neural Network Compression
Karen Ullrich, Edward Meeds, Max Welling
stat.MLcs.LGarXiv:1702.04008v22017
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
Daniel Ho, Eric Liang, Ion Stoica +2
cs.CVcs.LGstat.MLarXiv:1905.05393v12019
A* Sampling
Chris J. Maddison, Daniel Tarlow, Tom Minka
stat.COstat.MLarXiv:1411.0030v22014
MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection
Harsh Purohit, Ryo Tanabe, Kenji Ichige +4
cs.SDcs.LGeess.ASarXiv:1909.09347v12019
Data-Free Learning of Student Networks
Hanting Chen, Yunhe Wang, Chang Xu +6
cs.LGcs.CVstat.MLarXiv:1904.01186v42019
To understand deep learning we need to understand kernel learning
Mikhail Belkin, Siyuan Ma, Soumik Mandal
stat.MLcs.LGarXiv:1802.01396v32018
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data
Sergei Popov, Stanislav Morozov, Artem Babenko
cs.LGstat.MLarXiv:1909.06312v22019
Deep MIMO Detection
Neev Samuel, Tzvi Diskin, Ami Wiesel
stat.MLcs.ITcs.LGarXiv:1706.01151v12017
Learning Structural Node Embeddings Via Diffusion Wavelets
Claire Donnat, Marinka Zitnik, David Hallac +1
cs.SIcs.LGstat.MLarXiv:1710.10321v42017
Evaluating time series forecasting models: An empirical study on performance estimation methods
Vitor Cerqueira, Luis Torgo, Igor Mozetic
cs.LGstat.MLarXiv:1905.11744v12019
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning
Shakir Mohamed, Danilo Jimenez Rezende
stat.MLcs.AIcs.LGarXiv:1509.08731v12015
Predicting into unknown space? Estimating the area of applicability of spatial prediction models
Hanna Meyer, Edzer Pebesma
stat.MLcs.LGarXiv:2005.07939v12020
Pareto Multi-Task Learning
Xi Lin, Hui-Ling Zhen, Zhenhua Li +2
cs.LGstat.MLarXiv:1912.12854v12019
MAVEN: Multi-Agent Variational Exploration
Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan +1
cs.LGstat.MLarXiv:1910.07483v22019
Reliability-based design optimization using kriging surrogates and subset simulation
V. Dubourg, B. Sudret, J. -M. Bourinet
stat.MEstat.MLarXiv:1104.3667v12011
Amortised MAP Inference for Image Super-resolution
Casper Kaae Sønderby, Jose Caballero, Lucas Theis +2
cs.CVcs.LGstat.MLarXiv:1610.04490v32016
Comparing Rewinding and Fine-tuning in Neural Network Pruning
Alex Renda, Jonathan Frankle, Michael Carbin
cs.LGstat.MLarXiv:2003.02389v12020
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks
Mahdi Soltanolkotabi, Adel Javanmard, Jason D. Lee
cs.LGcs.ITmath.OCarXiv:1707.04926v32017
Why Is My Classifier Discriminatory?
Irene Chen, Fredrik D. Johansson, David Sontag
stat.MLcs.LGarXiv:1805.12002v22018
Online Identification and Tracking of Subspaces from Highly Incomplete Information
Laura Balzano, Robert Nowak, Benjamin Recht
cs.ITeess.SYmath.OCarXiv:1006.4046v22010
Canonical Tensor Decomposition for Knowledge Base Completion
Timothée Lacroix, Nicolas Usunier, Guillaume Obozinski
stat.MLcs.AIcs.LGarXiv:1806.07297v12018
Extended Isolation Forest
Sahand Hariri, Matias Carrasco Kind, Robert J. Brunner
cs.LGastro-ph.IMstat.MLarXiv:1811.02141v32018
Machine learning modeling of superconducting critical temperature
Valentin Stanev, Corey Oses, A. Gilad Kusne +4
cond-mat.supr-concond-mat.str-elstat.MLarXiv:1709.02727v22017
Global convergence of splitting methods for nonconvex composite optimization
Guoyin Li, Ting Kei Pong
math.OCcs.LGmath.NAarXiv:1407.0753v62014
Incremental Recommendation via Causal Models
Athanasios Vlontzos, David Gustafsson, Michael O'Riordan +1
stat.MLcs.LGstat.MEarXiv:2608.26804v12026
Interpretable machine learning: definitions, methods, and applications
W. James Murdoch, Chandan Singh, Karl Kumbier +2
stat.MLcs.AIcs.LGarXiv:1901.04592v12019
Prevalence of Neural Collapse during the terminal phase of deep learning training
Vardan Papyan, X. Y. Han, David L. Donoho
cs.LGcs.CVstat.MLarXiv:2008.08186v22020
Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning
Chi-Sing Ho, Neal Jean, Catherine A. Hogan +7
q-bio.QMcs.LGstat.MLarXiv:1901.07666v22019
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh +1
cs.LGcs.CVstat.MLarXiv:2005.04345v32020
The frontier of simulation-based inference
Kyle Cranmer, Johann Brehmer, Gilles Louppe
stat.MLcs.LGstat.MEarXiv:1911.01429v32019
AI safety via debate
Geoffrey Irving, Paul Christiano, Dario Amodei
stat.MLcs.LGarXiv:1805.00899v22018
Go-Explore: a New Approach for Hard-Exploration Problems
Adrien Ecoffet, Joost Huizinga, Joel Lehman +2
cs.LGcs.AIstat.MLarXiv:1901.10995v42019
Diagnosing and Enhancing VAE Models
Bin Dai, David Wipf
cs.LGcs.CVstat.MLarXiv:1903.05789v22019
Graph Convolutional Reinforcement Learning
Jiechuan Jiang, Chen Dun, Tiejun Huang +1
cs.LGcs.AIcs.MAarXiv:1810.09202v52018
Towards Physics-informed Deep Learning for Turbulent Flow Prediction
Rui Wang, Karthik Kashinath, Mustafa Mustafa +2
physics.comp-phcs.LGstat.MLarXiv:1911.08655v42019
Nonlinear unmixing of hyperspectral images: models and algorithms
Nicolas Dobigeon, Jean-Yves Tourneret, Cédric Richard +3
physics.data-anstat.APstat.MEarXiv:1304.1875v22013
COPOD: Copula-Based Outlier Detection
Zheng Li, Yue Zhao, Nicola Botta +2
stat.MLcs.IRcs.LGarXiv:2009.09463v12020
Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets
Penghang Yin, Jiancheng Lyu, Shuai Zhang +3
cs.LGmath.OCstat.MLarXiv:1903.05662v42019
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks
Difan Zou, Yuan Cao, Dongruo Zhou +1
cs.LGcs.AImath.OCarXiv:1811.08888v32018

Machine Learning (stat)

Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices

Is Pessimism Provably Efficient for Offline RL?

Learning to Perform Local Rewriting for Combinatorial Optimization

Robust Kernel Density Estimation

Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition

Stacked Bidirectional and Unidirectional LSTM Recurrent Neural Network for Forecasting Network-wide Traffic State with Missing Values

The Frontiers of Fairness in Machine Learning

Deep Kalman Filters

Fast and Accurate Recurrent Neural Network Acoustic Models for Speech Recognition

A Scalable Bootstrap for Massive Data

Learning in Implicit Generative Models

Neural networks for post-processing ensemble weather forecasts

Sequential Neural Models with Stochastic Layers

A survey of dimensionality reduction techniques

Towards a Neural Statistician

Is feature selection secure against training data poisoning?

Deep Learning of Vortex Induced Vibrations

Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models

Adversarial Policies: Attacking Deep Reinforcement Learning

Kernel and Rich Regimes in Overparametrized Models

Why not to use the Gaussian kernel

Soft Weight-Sharing for Neural Network Compression

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules

A* Sampling

MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection

Data-Free Learning of Student Networks

To understand deep learning we need to understand kernel learning

Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

Deep MIMO Detection

Learning Structural Node Embeddings Via Diffusion Wavelets

Evaluating time series forecasting models: An empirical study on performance estimation methods

Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning

Predicting into unknown space? Estimating the area of applicability of spatial prediction models

Pareto Multi-Task Learning

MAVEN: Multi-Agent Variational Exploration

Reliability-based design optimization using kriging surrogates and subset simulation

Amortised MAP Inference for Image Super-resolution

Comparing Rewinding and Fine-tuning in Neural Network Pruning

Theoretical insights into the optimization landscape of over-parameterized shallow neural networks

Why Is My Classifier Discriminatory?

Online Identification and Tracking of Subspaces from Highly Incomplete Information

Canonical Tensor Decomposition for Knowledge Base Completion

Extended Isolation Forest

Machine learning modeling of superconducting critical temperature

Global convergence of splitting methods for nonconvex composite optimization

Incremental Recommendation via Causal Models

Interpretable machine learning: definitions, methods, and applications

Prevalence of Neural Collapse during the terminal phase of deep learning training

Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning

An Investigation of Why Overparameterization Exacerbates Spurious Correlations

The frontier of simulation-based inference

AI safety via debate

Go-Explore: a New Approach for Hard-Exploration Problems

Diagnosing and Enhancing VAE Models

Graph Convolutional Reinforcement Learning

Towards Physics-informed Deep Learning for Turbulent Flow Prediction

Nonlinear unmixing of hyperspectral images: models and algorithms

COPOD: Copula-Based Outlier Detection

Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks