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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4,381 to 4,440 of 6,790

Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks
Reinhard Heckel, Paul Hand
cs.CVcs.LGstat.MLarXiv:1810.03982v22018
SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction
Hongwei Wang, Fuzheng Zhang, Min Hou +3
stat.MLcs.IRcs.LGarXiv:1712.00732v12017
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks
Pratik Chaudhari, Stefano Soatto
cs.LGcond-mat.stat-mechmath.OCarXiv:1710.11029v22017
Stochastic modified equations and adaptive stochastic gradient algorithms
Qianxiao Li, Cheng Tai, Weinan E
cs.LGstat.MLarXiv:1511.06251v32015
Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks
Yuhang Li, Xin Dong, Wei Wang
cs.LGstat.MLarXiv:1909.13144v22019
Learning De-biased Representations with Biased Representations
Hyojin Bahng, Sanghyuk Chun, Sangdoo Yun +2
cs.CVcs.LGstat.MLarXiv:1910.02806v32019
Bandits with heavy tail
Sébastien Bubeck, Nicolò Cesa-Bianchi, Gábor Lugosi
stat.MLcs.LGarXiv:1209.1727v12012
Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere
Jonathan A. Weyn, Dale R. Durran, Rich Caruana
physics.ao-phcs.LGstat.MLarXiv:2003.11927v12020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari +1
cs.LGcs.DCstat.MLarXiv:2007.01154v22020
Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining
Rajeev Yasarla, Vishal M. Patel
cs.CVcs.LGeess.IVarXiv:1906.11129v12019
WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving
Senthil Yogamani, Ciaran Hughes, Jonathan Horgan +14
cs.CVcs.AIcs.LGarXiv:1905.01489v32019
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
Martin Engelcke, Adam R. Kosiorek, Oiwi Parker Jones +1
cs.LGcs.CVcs.NEarXiv:1907.13052v42019
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient
Arnak S. Dalalyan, Avetik G. Karagulyan
math.STcs.LGmath.PRarXiv:1710.00095v42017
Character-based Neural Machine Translation
Marta R. Costa-Jussà, José A. R. Fonollosa
cs.CLcs.LGcs.NEarXiv:1603.00810v32016
Collaborative Filtering and the Missing at Random Assumption
Benjamin Marlin, Richard S. Zemel, Sam Roweis +1
cs.LGcs.IRstat.MLarXiv:1206.5267v12012
Speaker Diarization with LSTM
Quan Wang, Carlton Downey, Li Wan +2
eess.AScs.LGcs.SDarXiv:1710.10468v72017
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer
David Madras, Toniann Pitassi, Richard Zemel
stat.MLcs.LGarXiv:1711.06664v32017
Episodic Memory in Lifelong Language Learning
Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong +1
cs.LGcs.CLstat.MLarXiv:1906.01076v32019
Onsets and Frames: Dual-Objective Piano Transcription
Curtis Hawthorne, Erich Elsen, Jialin Song +6
cs.SDcs.LGeess.ASarXiv:1710.11153v22017
Unsupervised Semantic Segmentation by Distilling Feature Correspondences
Mark Hamilton, Zhoutong Zhang, Bharath Hariharan +2
cs.CVcs.AIcs.LGarXiv:2203.08414v12022
No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World
Shreya Shankar, Yoni Halpern, Eric Breck +3
stat.MLarXiv:1711.08536v12017
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Nic Ford, Justin Gilmer, Nicolas Carlini +1
cs.LGcs.CVstat.MLarXiv:1901.10513v12019
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
Difan Zou, Ziniu Hu, Yewen Wang +3
cs.LGcs.SIstat.MLarXiv:1911.07323v12019
Distributed Online Optimization in Dynamic Environments Using Mirror Descent
Shahin Shahrampour, Ali Jadbabaie
math.OCcs.DCcs.LGarXiv:1609.02845v12016
Structured sparsity through convex optimization
Francis Bach, Rodolphe Jenatton, Julien Mairal +1
cs.LGstat.MLarXiv:1109.2397v22011
Using Fast Weights to Attend to the Recent Past
Jimmy Ba, Geoffrey Hinton, Volodymyr Mnih +2
stat.MLcs.LGcs.NEarXiv:1610.06258v32016
Continuous Inverse Optimal Control with Locally Optimal Examples
Sergey Levine, Vladlen Koltun
cs.LGcs.AIstat.MLarXiv:1206.4617v12012
Differentially Private Learning Needs Better Features (or Much More Data)
Florian Tramèr, Dan Boneh
cs.LGcs.CRstat.MLarXiv:2011.11660v32020
Asymptotically Exact, Embarrassingly Parallel MCMC
Willie Neiswanger, Chong Wang, Eric Xing
stat.MLcs.DCcs.LGarXiv:1311.4780v22013
Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification
Liuyu Xiang, Guiguang Ding, Jungong Han
cs.CVcs.LGstat.MLarXiv:2001.01536v32020
Deep learning: a statistical viewpoint
Peter L. Bartlett, Andrea Montanari, Alexander Rakhlin
math.STcs.LGstat.MLarXiv:2103.09177v12021
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes
Xiaoyu Li, Francesco Orabona
stat.MLcs.LGmath.OCarXiv:1805.08114v32018
What graph neural networks cannot learn: depth vs width
Andreas Loukas
cs.LGstat.MLarXiv:1907.03199v22019
On Gridless Sparse Methods for Line Spectral Estimation From Complete and Incomplete Data
Zai Yang, Lihua Xie
cs.ITstat.MLarXiv:1407.2490v22014
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning
Sijia Liu, Pin-Yu Chen, Bhavya Kailkhura +3
cs.LGeess.SPstat.MLarXiv:2006.06224v22020
An exact mapping between the Variational Renormalization Group and Deep Learning
Pankaj Mehta, David J. Schwab
stat.MLcond-mat.stat-mechcs.LGarXiv:1410.3831v12014
ASD-DiagNet: A hybrid learning approach for detection of Autism Spectrum Disorder using fMRI data
Taban Eslami, Vahid Mirjalili, Alvis Fong +2
cs.LGeess.IVstat.MLarXiv:1904.07577v12019
Dual Discriminator Generative Adversarial Nets
Tu Dinh Nguyen, Trung Le, Hung Vu +1
cs.LGstat.MLarXiv:1709.03831v12017
The Discrete Gaussian for Differential Privacy
Clément L. Canonne, Gautam Kamath, Thomas Steinke
cs.DScs.CRstat.MLarXiv:2004.00010v62020
Machine learning for electronically excited states of molecules
Julia Westermayr, Philipp Marquetand
physics.chem-phstat.MLarXiv:2007.05320v12020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
Ines Chami, Sami Abu-El-Haija, Bryan Perozzi +2
cs.LGcs.NEcs.SIarXiv:2005.03675v32020
An introduction to domain adaptation and transfer learning
Wouter M. Kouw, Marco Loog
cs.LGcs.CVstat.MLarXiv:1812.11806v22018
Robustness via curvature regularization, and vice versa
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Jonathan Uesato +1
cs.LGcs.CVstat.MLarXiv:1811.09716v12018
Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection
Yu Bai, Fan Chen, Huan Wang +2
cs.LGcs.AIcs.CLarXiv:2306.04637v22023
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging
Mathias Perslev, Michael Hejselbak Jensen, Sune Darkner +2
cs.LGeess.SPstat.MLarXiv:1910.11162v12019
High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification
Edgar Dobriban, Stefan Wager
math.STstat.MLarXiv:1507.03003v22015
Elastic-Net Regularization in Learning Theory
C. De Mol, E. De Vito, L. Rosasco
stat.MLmath.STarXiv:0807.3423v12008
Jet-Images -- Deep Learning Edition
Luke de Oliveira, Michael Kagan, Lester Mackey +2
hep-phphysics.data-anstat.MLarXiv:1511.05190v32015
Understanding the Acceleration Phenomenon via High-Resolution Differential Equations
Bin Shi, Simon S. Du, Michael I. Jordan +1
math.OCcs.LGmath.CAarXiv:1810.08907v32018
Learning Robust Representations via Multi-View Information Bottleneck
Marco Federici, Anjan Dutta, Patrick Forré +2
cs.LGstat.MLarXiv:2002.07017v22020
Underdamped Langevin MCMC: A non-asymptotic analysis
Xiang Cheng, Niladri S. Chatterji, Peter L. Bartlett +1
stat.MLcs.LGstat.COarXiv:1707.03663v72017
Learning without Concentration
Shahar Mendelson
cs.LGstat.MLarXiv:1401.0304v22014
Learning Sparse Nonparametric DAGs
Xun Zheng, Chen Dan, Bryon Aragam +2
stat.MLcs.LGstat.MEarXiv:1909.13189v22019
First-order Methods for Geodesically Convex Optimization
Hongyi Zhang, Suvrit Sra
math.OCcs.LGstat.MLarXiv:1602.06053v12016
Proximal Newton-type methods for minimizing composite functions
Jason D. Lee, Yuekai Sun, Michael A. Saunders
stat.MLcs.DScs.LGarXiv:1206.1623v132012
Antisocial Behavior in Online Discussion Communities
Justin Cheng, Cristian Danescu-Niculescu-Mizil, Jure Leskovec
cs.SIcs.CYstat.AParXiv:1504.00680v22015
Causal inference using the algorithmic Markov condition
Dominik Janzing, Bernhard Schoelkopf
math.STcs.ITstat.MLarXiv:0804.3678v12008
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron
Sharan Vaswani, Francis Bach, Mark Schmidt
cs.LGstat.MLarXiv:1810.07288v32018
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift
Alekh Agarwal, Sham M. Kakade, Jason D. Lee +1
cs.LGstat.MLarXiv:1908.00261v52019
Vector Diffusion Maps and the Connection Laplacian
Amit Singer, Hau-tieng Wu
math.STstat.MLarXiv:1102.0075v12011

Machine Learning (stat)

Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks

SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction

Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks

Stochastic modified equations and adaptive stochastic gradient algorithms

Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Learning De-biased Representations with Biased Representations

Bandits with heavy tail

Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere

Federated Learning with Compression: Unified Analysis and Sharp Guarantees

Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining

WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving

GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations

User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient

Character-based Neural Machine Translation

Collaborative Filtering and the Missing at Random Assumption

Speaker Diarization with LSTM

Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer

Episodic Memory in Lifelong Language Learning

Onsets and Frames: Dual-Objective Piano Transcription

Unsupervised Semantic Segmentation by Distilling Feature Correspondences

No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World

Adversarial Examples Are a Natural Consequence of Test Error in Noise

Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks

Distributed Online Optimization in Dynamic Environments Using Mirror Descent

Structured sparsity through convex optimization

Using Fast Weights to Attend to the Recent Past

Continuous Inverse Optimal Control with Locally Optimal Examples

Differentially Private Learning Needs Better Features (or Much More Data)

Asymptotically Exact, Embarrassingly Parallel MCMC

Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification

Deep learning: a statistical viewpoint

On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes

What graph neural networks cannot learn: depth vs width

On Gridless Sparse Methods for Line Spectral Estimation From Complete and Incomplete Data

A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning

An exact mapping between the Variational Renormalization Group and Deep Learning

ASD-DiagNet: A hybrid learning approach for detection of Autism Spectrum Disorder using fMRI data

Dual Discriminator Generative Adversarial Nets

The Discrete Gaussian for Differential Privacy

Machine learning for electronically excited states of molecules

Machine Learning on Graphs: A Model and Comprehensive Taxonomy

An introduction to domain adaptation and transfer learning

Robustness via curvature regularization, and vice versa

Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging

High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification

Elastic-Net Regularization in Learning Theory

Jet-Images -- Deep Learning Edition

Understanding the Acceleration Phenomenon via High-Resolution Differential Equations

Learning Robust Representations via Multi-View Information Bottleneck

Underdamped Langevin MCMC: A non-asymptotic analysis

Learning without Concentration

Learning Sparse Nonparametric DAGs

First-order Methods for Geodesically Convex Optimization

Proximal Newton-type methods for minimizing composite functions

Antisocial Behavior in Online Discussion Communities

Causal inference using the algorithmic Markov condition

Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron

On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift

Vector Diffusion Maps and the Connection Laplacian