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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5,581 to 5,640 of 6,784

Principles and Practice of Explainable Machine Learning
Vaishak Belle, Ioannis Papantonis
cs.LGcs.AIstat.MLarXiv:2009.11698v12020
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
Fred Hohman, Minsuk Kahng, Robert Pienta +1
cs.HCcs.AIcs.LGarXiv:1801.06889v32018
The What-If Tool: Interactive Probing of Machine Learning Models
James Wexler, Mahima Pushkarna, Tolga Bolukbasi +3
cs.LGstat.MLarXiv:1907.04135v22019
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
Chen-Yu Lee, Tanmay Batra, Mohammad Haris Baig +1
cs.CVcs.LGstat.MLarXiv:1903.04064v12019
Efficient GAN-Based Anomaly Detection
Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat +2
cs.LGstat.MLarXiv:1802.06222v22018
Gradient Sparsification for Communication-Efficient Distributed Optimization
Jianqiao Wangni, Jialei Wang, Ji Liu +1
cs.LGmath.NAstat.MLarXiv:1710.09854v12017
Optimal rates for zero-order convex optimization: the power of two function evaluations
John C. Duchi, Michael I. Jordan, Martin J. Wainwright +1
math.OCcs.ITstat.MLarXiv:1312.2139v22013
Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles
Szilárd Aradi
cs.LGeess.SYstat.MLarXiv:2001.11231v12020
Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset
Curtis Hawthorne, Andriy Stasyuk, Adam Roberts +6
cs.SDcs.LGeess.ASarXiv:1810.12247v52018
Positive-Unlabeled Learning with Non-Negative Risk Estimator
Ryuichi Kiryo, Gang Niu, Marthinus C. du Plessis +1
cs.LGstat.MLarXiv:1703.00593v22017
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs
Xuhui Meng, Zhen Li, Dongkun Zhang +1
physics.comp-phcs.LGstat.MLarXiv:1909.10145v12019
Large-scale Multi-view Subspace Clustering in Linear Time
Zhao Kang, Wangtao Zhou, Zhitong Zhao +3
cs.LGcs.CVstat.MLarXiv:1911.09290v12019
On Smoothing and Inference for Topic Models
Arthur Asuncion, Max Welling, Padhraic Smyth +1
cs.LGstat.MLarXiv:1205.2662v12012
A review of domain adaptation without target labels
Wouter M. Kouw, Marco Loog
cs.LGstat.MLarXiv:1901.05335v22019
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
Tianyi Lin, Chi Jin, Michael I. Jordan
cs.LGmath.OCstat.MLarXiv:1906.00331v102019
On the (In)fidelity and Sensitivity for Explanations
Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala +2
cs.LGstat.MLarXiv:1901.09392v42019
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
Maurice Weiler, Mario Geiger, Max Welling +2
cs.LGstat.MLarXiv:1807.02547v22018
Generative Neural Networks for Sinkhorn Distributionally Robust Hypothesis Testing
Fenglin Zhang, Teyan Liu, Jie Wang
stat.MLcs.LGmath.OCarXiv:2608.22746v12026
Weight Poisoning Attacks on Pre-trained Models
Keita Kurita, Paul Michel, Graham Neubig
cs.LGcs.CLcs.CRarXiv:2004.06660v12020
On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests
Aaditya Ramdas, Nicolas Garcia, Marco Cuturi
math.STstat.MLarXiv:1509.02237v22015
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
Francesco Croce, Matthias Hein
cs.LGcs.CRcs.CVarXiv:1907.02044v22019
Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry
Maximilian Nickel, Douwe Kiela
cs.AIcs.LGstat.MLarXiv:1806.03417v22018
A review on longitudinal data analysis with random forest in precision medicine
Jianchang Hu, Silke Szymczak
stat.MLcs.LGarXiv:2208.04112v12022
PairNorm: Tackling Oversmoothing in GNNs
Lingxiao Zhao, Leman Akoglu
cs.LGstat.MLarXiv:1909.12223v22019
MONet: Unsupervised Scene Decomposition and Representation
Christopher P. Burgess, Loic Matthey, Nicholas Watters +4
cs.CVcs.LGstat.MLarXiv:1901.11390v12019
A review: Deep learning for medical image segmentation using multi-modality fusion
Tongxue Zhou, Su Ruan, Stéphane Canu
eess.IVcs.CVcs.LGarXiv:2004.10664v22020
Unbiased Offline Evaluation of Contextual-bandit-based News Article Recommendation Algorithms
Lihong Li, Wei Chu, John Langford +1
cs.LGcs.AIcs.ROarXiv:1003.5956v22010
Deep Learning in Medical Image Registration: A Review
Yabo Fu, Yang Lei, Tonghe Wang +3
eess.IVcs.CVcs.LGarXiv:1912.12318v12019
Gaussian Process Behaviour in Wide Deep Neural Networks
Alexander G. de G. Matthews, Mark Rowland, Jiri Hron +2
stat.MLcs.LGarXiv:1804.11271v22018
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
Yunbo Wang, Zhifeng Gao, Mingsheng Long +2
cs.LGcs.CVstat.MLarXiv:1804.06300v22018
Neural Processes
Marta Garnelo, Jonathan Schwarz, Dan Rosenbaum +4
cs.LGstat.MLarXiv:1807.01622v12018
Grad-CAM: Why did you say that?
Ramprasaath R Selvaraju, Abhishek Das, Ramakrishna Vedantam +3
stat.MLcs.CVcs.LGarXiv:1611.07450v22016
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets
Aaron Klein, Stefan Falkner, Simon Bartels +2
cs.LGcs.AIstat.MLarXiv:1605.07079v22016
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
Daniel Borkan, Lucas Dixon, Jeffrey Sorensen +2
cs.LGcs.CLstat.MLarXiv:1903.04561v22019
Generative and Discriminative Voxel Modeling with Convolutional Neural Networks
Andrew Brock, Theodore Lim, J. M. Ritchie +1
cs.CVcs.HCcs.LGarXiv:1608.04236v22016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods
Zeyuan Allen-Zhu
math.OCcs.DScs.LGarXiv:1603.05953v62016
Scalable agent alignment via reward modeling: a research direction
Jan Leike, David Krueger, Tom Everitt +3
cs.LGcs.AIcs.NEarXiv:1811.07871v12018
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons
Byeongho Heo, Minsik Lee, Sangdoo Yun +1
cs.LGcs.CVstat.MLarXiv:1811.03233v22018
Structured Variable Selection with Sparsity-Inducing Norms
Rodolphe Jenatton, Jean-Yves Audibert, Francis Bach
stat.MLarXiv:0904.3523v32009
Reliable Fidelity and Diversity Metrics for Generative Models
Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh +2
cs.CVcs.LGstat.MLarXiv:2002.09797v22020
Lagrangian Neural Networks
Miles Cranmer, Sam Greydanus, Stephan Hoyer +3
cs.LGmath.DSphysics.comp-pharXiv:2003.04630v22020
Sequence-to-Sequence Learning as Beam-Search Optimization
Sam Wiseman, Alexander M. Rush
cs.CLcs.LGcs.NEarXiv:1606.02960v22016
The UEA multivariate time series classification archive, 2018
Anthony Bagnall, Hoang Anh Dau, Jason Lines +5
cs.LGstat.MLarXiv:1811.00075v12018
Sequential operator learning under dependent data
Rafael Oliveira
stat.MLcs.LGarXiv:2608.24426v12026
Neural Additive Models: Interpretable Machine Learning with Neural Nets
Rishabh Agarwal, Levi Melnick, Nicholas Frosst +4
cs.LGcs.AIstat.MLarXiv:2004.13912v22020
Learning to Optimize
Ke Li, Jitendra Malik
cs.LGcs.AImath.OCarXiv:1606.01885v12016
Residual Gated Graph ConvNets
Xavier Bresson, Thomas Laurent
cs.LGstat.MLarXiv:1711.07553v22017
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks
Sunil Thulasidasan, Gopinath Chennupati, Jeff Bilmes +2
stat.MLcs.LGarXiv:1905.11001v52019
Why do tree-based models still outperform deep learning on tabular data?
Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux
cs.LGcs.AIstat.MEarXiv:2207.08815v12022
Distral: Robust Multitask Reinforcement Learning
Yee Whye Teh, Victor Bapst, Wojciech Marian Czarnecki +5
cs.LGstat.MLarXiv:1707.04175v12017
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem
Matthias Hein, Maksym Andriushchenko, Julian Bitterwolf
cs.LGcs.CVstat.MLarXiv:1812.05720v22018
StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis
Jiatao Gu, Lingjie Liu, Peng Wang +1
cs.CVstat.MLarXiv:2110.08985v12021
Empirical Bernstein Bounds and Sample Variance Penalization
Andreas Maurer, Massimiliano Pontil
stat.MLarXiv:0907.3740v12009
Simplicial Closure and higher-order link prediction
Austin R. Benson, Rediet Abebe, Michael T. Schaub +2
cs.SIcond-mat.stat-mechmath.ATarXiv:1802.06916v22018
Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey
Ammar Haydari, Yasin Yilmaz
cs.LGcs.MAeess.SParXiv:2005.00935v12020
What is being transferred in transfer learning?
Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang
cs.LGstat.MLarXiv:2008.11687v22020
Matrix Completion has No Spurious Local Minimum
Rong Ge, Jason D. Lee, Tengyu Ma
cs.LGcs.DSstat.MLarXiv:1605.07272v42016
Regularisation of Neural Networks by Enforcing Lipschitz Continuity
Henry Gouk, Eibe Frank, Bernhard Pfahringer +1
stat.MLcs.LGarXiv:1804.04368v32018
Medical image denoising using convolutional denoising autoencoders
Lovedeep Gondara
cs.CVstat.MLarXiv:1608.04667v22016
Revealing the Dark Secrets of BERT
Olga Kovaleva, Alexey Romanov, Anna Rogers +1
cs.CLcs.LGstat.MLarXiv:1908.08593v22019

Machine Learning (stat)

Principles and Practice of Explainable Machine Learning

Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers

The What-If Tool: Interactive Probing of Machine Learning Models

Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation

Efficient GAN-Based Anomaly Detection

Gradient Sparsification for Communication-Efficient Distributed Optimization

Optimal rates for zero-order convex optimization: the power of two function evaluations

Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles

Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset

Positive-Unlabeled Learning with Non-Negative Risk Estimator

PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs

Large-scale Multi-view Subspace Clustering in Linear Time

On Smoothing and Inference for Topic Models

A review of domain adaptation without target labels

On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems

On the (In)fidelity and Sensitivity for Explanations

3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data

Generative Neural Networks for Sinkhorn Distributionally Robust Hypothesis Testing

Weight Poisoning Attacks on Pre-trained Models

On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests

Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack

Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry

A review on longitudinal data analysis with random forest in precision medicine

PairNorm: Tackling Oversmoothing in GNNs

MONet: Unsupervised Scene Decomposition and Representation

A review: Deep learning for medical image segmentation using multi-modality fusion

Unbiased Offline Evaluation of Contextual-bandit-based News Article Recommendation Algorithms

Deep Learning in Medical Image Registration: A Review

Gaussian Process Behaviour in Wide Deep Neural Networks

PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning

Neural Processes

Grad-CAM: Why did you say that?

Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets

Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification

Generative and Discriminative Voxel Modeling with Convolutional Neural Networks

Katyusha: The First Direct Acceleration of Stochastic Gradient Methods

Scalable agent alignment via reward modeling: a research direction

Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons

Structured Variable Selection with Sparsity-Inducing Norms

Reliable Fidelity and Diversity Metrics for Generative Models

Lagrangian Neural Networks

Sequence-to-Sequence Learning as Beam-Search Optimization

The UEA multivariate time series classification archive, 2018

Sequential operator learning under dependent data

Neural Additive Models: Interpretable Machine Learning with Neural Nets

Learning to Optimize

Residual Gated Graph ConvNets

On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks

Why do tree-based models still outperform deep learning on tabular data?

Distral: Robust Multitask Reinforcement Learning

Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem

StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis

Empirical Bernstein Bounds and Sample Variance Penalization

Simplicial Closure and higher-order link prediction

Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey

What is being transferred in transfer learning?

Matrix Completion has No Spurious Local Minimum

Regularisation of Neural Networks by Enforcing Lipschitz Continuity

Medical image denoising using convolutional denoising autoencoders

Revealing the Dark Secrets of BERT