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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4,741 to 4,800 of 6,790

BilBOWA: Fast Bilingual Distributed Representations without Word Alignments
Stephan Gouws, Yoshua Bengio, Greg Corrado
stat.MLcs.CLcs.LGarXiv:1410.2455v32014
Animating Arbitrary Objects via Deep Motion Transfer
Aliaksandr Siarohin, Stéphane Lathuilière, Sergey Tulyakov +2
cs.GRcs.CVcs.LGarXiv:1812.08861v32018
Survey of Personalization Techniques for Federated Learning
Viraj Kulkarni, Milind Kulkarni, Aniruddha Pant
cs.LGstat.MLarXiv:2003.08673v12020
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems
David R. Karger, Sewoong Oh, Devavrat Shah
cs.LGcs.DScs.HCarXiv:1110.3564v42011
Stochastic Variational Bayesian Inference for a Nonlinear Forward Model
Michael A. Chappell, Martin S. Craig, Mark W. Woolrich
eess.SPstat.APstat.MLarXiv:2007.01675v12020
Certified Adversarial Robustness with Additive Noise
Bai Li, Changyou Chen, Wenlin Wang +1
cs.LGcs.CRstat.MLarXiv:1809.03113v62018
Critic Regularized Regression
Ziyu Wang, Alexander Novikov, Konrad Zolna +8
cs.LGcs.AIstat.MLarXiv:2006.15134v32020
Topology Adaptive Graph Convolutional Networks
Jian Du, Shanghang Zhang, Guanhang Wu +2
cs.LGstat.MLarXiv:1710.10370v52017
MoFlow: An Invertible Flow Model for Generating Molecular Graphs
Chengxi Zang, Fei Wang
stat.MLcs.LGphysics.chem-pharXiv:2006.10137v12020
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data
Marc Finzi, Samuel Stanton, Pavel Izmailov +1
stat.MLcs.LGarXiv:2002.12880v32020
Adaptive Gradient-Based Meta-Learning Methods
Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar
cs.LGcs.AIstat.MLarXiv:1906.02717v32019
mm-Pose: Real-Time Human Skeletal Posture Estimation using mmWave Radars and CNNs
Arindam Sengupta, Feng Jin, Renyuan Zhang +1
eess.SPcs.LGstat.MLarXiv:1911.09592v12019
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
Carlos Riquelme, George Tucker, Jasper Snoek
stat.MLcs.LGarXiv:1802.09127v12018
Graph Wavelet Neural Network
Bingbing Xu, Huawei Shen, Qi Cao +2
cs.LGstat.MLarXiv:1904.07785v12019
A Stable Multi-Scale Kernel for Topological Machine Learning
Jan Reininghaus, Stefan Huber, Ulrich Bauer +1
stat.MLcs.CVcs.LGarXiv:1412.6821v12014
Improving Deep Learning using Generic Data Augmentation
Luke Taylor, Geoff Nitschke
cs.LGstat.MLarXiv:1708.06020v12017
Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
Boris Hanin
stat.MLcs.CGcs.LGarXiv:1708.02691v32017
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks
Mingchen Li, Mahdi Soltanolkotabi, Samet Oymak
cs.LGstat.MLarXiv:1903.11680v32019
Rank consistent ordinal regression for neural networks with application to age estimation
Wenzhi Cao, Vahid Mirjalili, Sebastian Raschka
cs.LGstat.MLarXiv:1901.07884v72019
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods
Maher Nouiehed, Maziar Sanjabi, Tianjian Huang +2
math.OCcs.LGstat.MLarXiv:1902.08297v32019
Introduction to Multi-Armed Bandits
Aleksandrs Slivkins
cs.LGcs.AIcs.DSarXiv:1904.07272v82019
Snorkel: Rapid Training Data Creation with Weak Supervision
Alexander Ratner, Stephen H. Bach, Henry Ehrenberg +3
cs.LGstat.MLarXiv:1711.10160v12017
Unsupervised Domain Adaptation by Backpropagation
Yaroslav Ganin, Victor Lempitsky
stat.MLcs.LGcs.NEarXiv:1409.7495v22014
Collaborative Deep Learning for Recommender Systems
Hao Wang, Naiyan Wang, Dit-Yan Yeung
cs.LGcs.CLcs.IRarXiv:1409.2944v22014
Engaging with Massive Online Courses
Ashton Anderson, Daniel Huttenlocher, Jon Kleinberg +1
cs.SIphysics.soc-phstat.MLarXiv:1403.3100v22014
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation
Qiang Liu, Lihong Li, Ziyang Tang +1
cs.LGcs.AIeess.SYarXiv:1810.12429v12018
MLPerf Training Benchmark
Peter Mattson, Christine Cheng, Cody Coleman +34
cs.LGcs.PFstat.MLarXiv:1910.01500v32019
GRAND: Graph Neural Diffusion
Benjamin Paul Chamberlain, James Rowbottom, Maria Gorinova +3
cs.LGstat.MLarXiv:2106.10934v22021
The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures
Anne-Claire Haury, Pierre Gestraud, Jean-Philippe Vert
q-bio.QMstat.APstat.MLarXiv:1101.5008v22011
InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions
Shikhar Vashishth, Soumya Sanyal, Vikram Nitin +2
cs.LGstat.MLarXiv:1911.00219v32019
Deepr: A Convolutional Net for Medical Records
Phuoc Nguyen, Truyen Tran, Nilmini Wickramasinghe +1
stat.MLcs.LGarXiv:1607.07519v12016
Fairness without Demographics through Adversarially Reweighted Learning
Preethi Lahoti, Alex Beutel, Jilin Chen +5
cs.LGstat.MLarXiv:2006.13114v32020
Learning to Predict Indoor Illumination from a Single Image
Marc-André Gardner, Kalyan Sunkavalli, Ersin Yumer +4
cs.CVcs.GRstat.MLarXiv:1704.00090v32017
Controllable Multi-Interest Framework for Recommendation
Yukuo Cen, Jianwei Zhang, Xu Zou +3
cs.IRcs.LGstat.MLarXiv:2005.09347v22020
Absence of Barren Plateaus in Quantum Convolutional Neural Networks
Arthur Pesah, M. Cerezo, Samson Wang +3
quant-phcs.LGstat.MLarXiv:2011.02966v22020
Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog
Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen +5
cs.LGcs.AIstat.MLarXiv:1907.00456v22019
Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification
Huy Phan, Fernando Andreotti, Navin Cooray +2
cs.LGstat.MLarXiv:1805.06546v32018
Smart Augmentation - Learning an Optimal Data Augmentation Strategy
Joseph Lemley, Shabab Bazrafkan, Peter Corcoran
cs.AIcs.LGstat.MLarXiv:1703.08383v12017
A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction
Thomas Wiatowski, Helmut Bölcskei
cs.ITcs.AIcs.LGarXiv:1512.06293v32015
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization
Samuel Daulton, Maximilian Balandat, Eytan Bakshy
stat.MLcs.AIcs.LGarXiv:2006.05078v32020
The Cramer Distance as a Solution to Biased Wasserstein Gradients
Marc G. Bellemare, Ivo Danihelka, Will Dabney +4
cs.LGstat.MLarXiv:1705.10743v12017
Convolutional Kernel Networks
Julien Mairal, Piotr Koniusz, Zaid Harchaoui +1
cs.CVcs.LGstat.MLarXiv:1406.3332v22014
Path-Specific Counterfactual Fairness
Silvia Chiappa, Thomas P. S. Gillam
stat.MLarXiv:1802.08139v12018
High Dimensional Semiparametric Gaussian Copula Graphical Models
Han Liu, Fang Han, Ming Yuan +2
stat.MLarXiv:1202.2169v32012
Generalized double Pareto shrinkage
Artin Armagan, David Dunson, Jaeyong Lee
stat.MEmath.STstat.MLarXiv:1104.0861v42011
Representation Measurements Under Function-Preserving Reparameterizations
Abdullah Karasan
stat.MLcs.LGarXiv:2608.27020v12026
Slow Learners are Fast
John Langford, Alexander Smola, Martin Zinkevich
math.OCstat.MLarXiv:0911.0491v12009
Generalized Sliced Wasserstein Distances
Soheil Kolouri, Kimia Nadjahi, Umut Simsekli +2
cs.LGstat.MLarXiv:1902.00434v12019
Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel +1
cs.LGcs.AIcs.CVarXiv:2009.08319v32020
Super-Samples from Kernel Herding
Yutian Chen, Max Welling, Alex Smola
cs.LGstat.MLarXiv:1203.3472v12012
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Julius von Kügelgen, Yash Sharma, Luigi Gresele +4
stat.MLcs.AIcs.CVarXiv:2106.04619v42021
D$^2$: Decentralized Training over Decentralized Data
Hanlin Tang, Xiangru Lian, Ming Yan +2
cs.DCcs.LGstat.MLarXiv:1803.07068v22018
Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks
Behnam Neyshabur, Zhiyuan Li, Srinadh Bhojanapalli +2
cs.LGstat.MLarXiv:1805.12076v12018
Robustness of classifiers: from adversarial to random noise
Alhussein Fawzi, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard
cs.LGcs.CVstat.MLarXiv:1608.08967v12016
Understanding Attention and Generalization in Graph Neural Networks
Boris Knyazev, Graham W. Taylor, Mohamed R. Amer
cs.LGcs.AIstat.MLarXiv:1905.02850v32019
TensorFlow Distributions
Joshua V. Dillon, Ian Langmore, Dustin Tran +7
cs.LGcs.AIcs.PLarXiv:1711.10604v12017
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks
Xiang Zhang, Marinka Zitnik
cs.LGstat.MLarXiv:2006.08149v32020
Whitening for Self-Supervised Representation Learning
Aleksandr Ermolov, Aliaksandr Siarohin, Enver Sangineto +1
cs.LGcs.CVstat.MLarXiv:2007.06346v52020
Distance Dependent Chinese Restaurant Processes
David M. Blei, Peter I. Frazier
stat.MLstat.MEarXiv:0910.1022v32009
Federated Multi-Task Learning under a Mixture of Distributions
Othmane Marfoq, Giovanni Neglia, Aurélien Bellet +2
cs.LGcs.AImath.OCarXiv:2108.10252v42021

Machine Learning (stat)

BilBOWA: Fast Bilingual Distributed Representations without Word Alignments

Animating Arbitrary Objects via Deep Motion Transfer

Survey of Personalization Techniques for Federated Learning

Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems

Stochastic Variational Bayesian Inference for a Nonlinear Forward Model

Certified Adversarial Robustness with Additive Noise

Critic Regularized Regression

Topology Adaptive Graph Convolutional Networks

MoFlow: An Invertible Flow Model for Generating Molecular Graphs

Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data

Adaptive Gradient-Based Meta-Learning Methods

mm-Pose: Real-Time Human Skeletal Posture Estimation using mmWave Radars and CNNs

Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling

Graph Wavelet Neural Network

A Stable Multi-Scale Kernel for Topological Machine Learning

Improving Deep Learning using Generic Data Augmentation

Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations

Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks

Rank consistent ordinal regression for neural networks with application to age estimation

Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods

Introduction to Multi-Armed Bandits

Snorkel: Rapid Training Data Creation with Weak Supervision

Unsupervised Domain Adaptation by Backpropagation

Collaborative Deep Learning for Recommender Systems

Engaging with Massive Online Courses

Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation

MLPerf Training Benchmark

GRAND: Graph Neural Diffusion

The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures

InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions

Deepr: A Convolutional Net for Medical Records

Fairness without Demographics through Adversarially Reweighted Learning

Learning to Predict Indoor Illumination from a Single Image

Controllable Multi-Interest Framework for Recommendation

Absence of Barren Plateaus in Quantum Convolutional Neural Networks

Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog

Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

Smart Augmentation - Learning an Optimal Data Augmentation Strategy

A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction

Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization

The Cramer Distance as a Solution to Biased Wasserstein Gradients

Convolutional Kernel Networks

Path-Specific Counterfactual Fairness

High Dimensional Semiparametric Gaussian Copula Graphical Models

Generalized double Pareto shrinkage

Representation Measurements Under Function-Preserving Reparameterizations

Slow Learners are Fast

Generalized Sliced Wasserstein Distances

Decoupling Representation Learning from Reinforcement Learning

Super-Samples from Kernel Herding

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style

D$^2$: Decentralized Training over Decentralized Data

Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks

Robustness of classifiers: from adversarial to random noise

Understanding Attention and Generalization in Graph Neural Networks

TensorFlow Distributions

GNNGuard: Defending Graph Neural Networks against Adversarial Attacks

Whitening for Self-Supervised Representation Learning

Distance Dependent Chinese Restaurant Processes

Federated Multi-Task Learning under a Mixture of Distributions