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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3,781 to 3,840 of 6,780

UR-FUNNY: A Multimodal Language Dataset for Understanding Humor
Md Kamrul Hasan, Wasifur Rahman, Amir Zadeh +5
cs.LGcs.CLstat.MLarXiv:1904.06618v12019
Adversarial Examples: Opportunities and Challenges
Jiliang Zhang, Chen Li
cs.LGstat.MLarXiv:1809.04790v42018
Variational Quantum Algorithms
M. Cerezo, Andrew Arrasmith, Ryan Babbush +8
quant-phcs.LGstat.MLarXiv:2012.09265v22020
How to Start Training: The Effect of Initialization and Architecture
Boris Hanin, David Rolnick
stat.MLcs.LGarXiv:1803.01719v32018
Machine Learning for Reliability Engineering and Safety Applications: Review of Current Status and Future Opportunities
Zhaoyi Xu, Joseph Homer Saleh
cs.LGstat.MLarXiv:2008.08221v12020
Machine Learning for Fluid Mechanics
Steven Brunton, Bernd Noack, Petros Koumoutsakos
physics.flu-dyncs.LGstat.MLarXiv:1905.11075v32019
DSTP-RNN: a dual-stage two-phase attention-based recurrent neural networks for long-term and multivariate time series prediction
Yeqi Liu, Chuanyang Gong, Ling Yang +1
cs.LGstat.MLarXiv:1904.07464v12019
PyTorch-BigGraph: A Large-scale Graph Embedding System
Adam Lerer, Ledell Wu, Jiajun Shen +4
cs.LGcs.AIcs.DCarXiv:1903.12287v32019
A Multi-Horizon Quantile Recurrent Forecaster
Ruofeng Wen, Kari Torkkola, Balakrishnan Narayanaswamy +1
stat.MLarXiv:1711.11053v22017
Network Sampling: From Static to Streaming Graphs
Nesreen K. Ahmed, Jennifer Neville, Ramana Kompella
cs.SIcs.DScs.LGarXiv:1211.3412v12012
Asymmetric Deep Supervised Hashing
Qing-Yuan Jiang, Wu-Jun Li
cs.LGstat.MLarXiv:1707.08325v12017
Theory of overparametrization in quantum neural networks
Martin Larocca, Nathan Ju, Diego García-Martín +2
quant-phcs.LGstat.MLarXiv:2109.11676v12021
Transformers without Tears: Improving the Normalization of Self-Attention
Toan Q. Nguyen, Julian Salazar
cs.CLcs.LGstat.MLarXiv:1910.05895v22019
A Robust Learning Approach to Domain Adaptive Object Detection
Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar +1
cs.LGcs.CVstat.MLarXiv:1904.02361v32019
Unsupervised State Representation Learning in Atari
Ankesh Anand, Evan Racah, Sherjil Ozair +3
cs.LGstat.MLarXiv:1906.08226v62019
Fast and Accurate Time Series Classification with WEASEL
Patrick Schäfer, Ulf Leser
cs.DScs.LGstat.MLarXiv:1701.07681v12017
Fast Algorithms for Robust PCA via Gradient Descent
Xinyang Yi, Dohyung Park, Yudong Chen +1
cs.ITcs.LGmath.STarXiv:1605.07784v22016
The Privacy Blanket of the Shuffle Model
Borja Balle, James Bell, Adria Gascon +1
cs.LGcs.CRstat.MLarXiv:1903.02837v22019
Generative adversarial networks (GAN) based efficient sampling of chemical space for inverse design of inorganic materials
Yabo Dan, Yong Zhao, Xiang Li +3
cs.LGcs.NEstat.MLarXiv:1911.05020v12019
Foolbox: A Python toolbox to benchmark the robustness of machine learning models
Jonas Rauber, Wieland Brendel, Matthias Bethge
cs.LGcs.CRcs.CVarXiv:1707.04131v32017
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes
David Salinas, Michael Bohlke-Schneider, Laurent Callot +2
cs.LGstat.MLarXiv:1910.03002v22019
Gradient Descent for Spiking Neural Networks
Dongsung Huh, Terrence J. Sejnowski
q-bio.NCcs.LGcs.NEarXiv:1706.04698v22017
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III
Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan +3
cs.LGstat.MLarXiv:1907.08322v22019
Deep Reinforcement Learning Based Dynamic Trajectory Control for UAV-assisted Mobile Edge Computing
Liang Wang, Kezhi Wang, Cunhua Pan +3
eess.SPcs.LGcs.NIarXiv:1911.03887v22019
Online Learning Rate Adaptation with Hypergradient Descent
Atilim Gunes Baydin, Robert Cornish, David Martinez Rubio +2
cs.LGstat.MLarXiv:1703.04782v32017
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning
Wonyong Jeong, Jaehong Yoon, Eunho Yang +1
cs.LGstat.MLarXiv:2006.12097v32020
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text
Koustuv Sinha, Shagun Sodhani, Jin Dong +2
cs.LGcs.CLcs.LOarXiv:1908.06177v22019
Guided Conditional Diffusion for Controllable Traffic Simulation
Ziyuan Zhong, Davis Rempe, Danfei Xu +5
cs.ROcs.AIcs.LGarXiv:2210.17366v12022
Uncovering the structure of clinical EEG signals with self-supervised learning
Hubert Banville, Omar Chehab, Aapo Hyvärinen +2
stat.MLcs.LGeess.SParXiv:2007.16104v12020
A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME
Ahmed Salih, Zahra Raisi-Estabragh, Ilaria Boscolo Galazzo +4
stat.MLcs.AIcs.LGarXiv:2305.02012v32023
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices
Caiwen Ding, Siyu Liao, Yanzhi Wang +13
cs.CVcs.AIcs.LGarXiv:1708.08917v12017
Data-driven Advice for Applying Machine Learning to Bioinformatics Problems
Randal S. Olson, William La Cava, Zairah Mustahsan +2
q-bio.QMcs.LGstat.MLarXiv:1708.05070v22017
Effect of barren plateaus on gradient-free optimization
Andrew Arrasmith, M. Cerezo, Piotr Czarnik +2
quant-phcs.LGstat.MLarXiv:2011.12245v22020
Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks
Haoran You, Chaojian Li, Pengfei Xu +6
cs.LGstat.MLarXiv:1909.11957v62019
Deep Learning for Financial Applications : A Survey
Ahmet Murat Ozbayoglu, Mehmet Ugur Gudelek, Omer Berat Sezer
q-fin.STcs.LGstat.MLarXiv:2002.05786v12020
Insertion Transformer: Flexible Sequence Generation via Insertion Operations
Mitchell Stern, William Chan, Jamie Kiros +1
cs.CLcs.LGstat.MLarXiv:1902.03249v12019
Deep Neural Networks Motivated by Partial Differential Equations
Lars Ruthotto, Eldad Haber
cs.LGmath.OCstat.MLarXiv:1804.04272v22018
The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods
Jaime Lorenzo-Trueba, Junichi Yamagishi, Tomoki Toda +4
eess.AScs.CLcs.SDarXiv:1804.04262v12018
Playing hard exploration games by watching YouTube
Yusuf Aytar, Tobias Pfaff, David Budden +3
cs.LGcs.AIcs.CVarXiv:1805.11592v22018
Structure and inference in annotated networks
M. E. J. Newman, Aaron Clauset
cs.SIphysics.data-anphysics.soc-pharXiv:1507.04001v12015
Freeze-Thaw Bayesian Optimization
Kevin Swersky, Jasper Snoek, Ryan Prescott Adams
stat.MLcs.LGarXiv:1406.3896v12014
Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning
Jiwoong Park, Minsik Lee, Hyung Jin Chang +2
cs.LGcs.CVstat.MLarXiv:1908.02441v12019
Universal Language Model Fine-tuning for Text Classification
Jeremy Howard, Sebastian Ruder
cs.CLcs.LGstat.MLarXiv:1801.06146v52018
Feature-Critic Networks for Heterogeneous Domain Generalization
Yiying Li, Yongxin Yang, Wei Zhou +1
cs.LGstat.MLarXiv:1901.11448v32019
Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer
David Berthelot, Colin Raffel, Aurko Roy +1
cs.LGstat.MLarXiv:1807.07543v22018
Complexity of Linear Regions in Deep Networks
Boris Hanin, David Rolnick
stat.MLcs.LGmath.PRarXiv:1901.09021v22019
Broadband DOA estimation using Convolutional neural networks trained with noise signals
Soumitro Chakrabarty, Emanuël. A. P. Habets
cs.SDstat.MLarXiv:1705.00919v22017
Understanding Probabilistic Sparse Gaussian Process Approximations
Matthias Bauer, Mark van der Wilk, Carl Edward Rasmussen
stat.MLarXiv:1606.04820v22016
End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances
Marin Toromanoff, Emilie Wirbel, Fabien Moutarde
cs.LGcs.AIcs.CVarXiv:1911.10868v22019
Neural Jump Stochastic Differential Equations
Junteng Jia, Austin R. Benson
cs.LGstat.MLarXiv:1905.10403v32019
Bike Flow Prediction with Multi-Graph Convolutional Networks
Di Chai, Leye Wang, Qiang Yang
cs.LGcs.AIstat.MLarXiv:1807.10934v12018
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks
Itay Safran, Ohad Shamir
cs.LGstat.MLarXiv:1712.08968v32017
Adaptive Aggregation Networks for Class-Incremental Learning
Yaoyao Liu, Bernt Schiele, Qianru Sun
cs.CVstat.MLarXiv:2010.05063v32020
Inductive Matrix Completion Based on Graph Neural Networks
Muhan Zhang, Yixin Chen
cs.IRcs.LGstat.MLarXiv:1904.12058v32019
Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learning
Saiprasad Ravishankar, Jong Chul Ye, Jeffrey A. Fessler
eess.IVcs.LGstat.MLarXiv:1904.02816v32019
What Can Neural Networks Reason About?
Keyulu Xu, Jingling Li, Mozhi Zhang +3
cs.LGcs.AIcs.CVarXiv:1905.13211v42019
Benchmarking Simulation-Based Inference
Jan-Matthis Lueckmann, Jan Boelts, David S. Greenberg +2
stat.MLcs.LGarXiv:2101.04653v22021
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans
Gamaleldin F. Elsayed, Shreya Shankar, Brian Cheung +4
cs.LGcs.CVq-bio.NCarXiv:1802.08195v32018
EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals
Kay Gregor Hartmann, Robin Tibor Schirrmeister, Tonio Ball
eess.SPcs.LGq-bio.NCarXiv:1806.01875v12018
Differentiable Causal Discovery from Interventional Data
Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste +2
cs.LGstat.MLarXiv:2007.01754v22020

Machine Learning (stat)

UR-FUNNY: A Multimodal Language Dataset for Understanding Humor

Adversarial Examples: Opportunities and Challenges

Variational Quantum Algorithms

How to Start Training: The Effect of Initialization and Architecture

Machine Learning for Reliability Engineering and Safety Applications: Review of Current Status and Future Opportunities

Machine Learning for Fluid Mechanics

DSTP-RNN: a dual-stage two-phase attention-based recurrent neural networks for long-term and multivariate time series prediction

PyTorch-BigGraph: A Large-scale Graph Embedding System

A Multi-Horizon Quantile Recurrent Forecaster

Network Sampling: From Static to Streaming Graphs

Asymmetric Deep Supervised Hashing

Theory of overparametrization in quantum neural networks

Transformers without Tears: Improving the Normalization of Self-Attention

A Robust Learning Approach to Domain Adaptive Object Detection

Unsupervised State Representation Learning in Atari

Fast and Accurate Time Series Classification with WEASEL

Fast Algorithms for Robust PCA via Gradient Descent

The Privacy Blanket of the Shuffle Model

Generative adversarial networks (GAN) based efficient sampling of chemical space for inverse design of inorganic materials

Foolbox: A Python toolbox to benchmark the robustness of machine learning models

High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes

Gradient Descent for Spiking Neural Networks

MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III

Deep Reinforcement Learning Based Dynamic Trajectory Control for UAV-assisted Mobile Edge Computing

Online Learning Rate Adaptation with Hypergradient Descent

Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text

Guided Conditional Diffusion for Controllable Traffic Simulation

Uncovering the structure of clinical EEG signals with self-supervised learning

A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME

CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices

Data-driven Advice for Applying Machine Learning to Bioinformatics Problems

Effect of barren plateaus on gradient-free optimization

Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks

Deep Learning for Financial Applications : A Survey

Insertion Transformer: Flexible Sequence Generation via Insertion Operations

Deep Neural Networks Motivated by Partial Differential Equations

The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods

Playing hard exploration games by watching YouTube

Structure and inference in annotated networks

Freeze-Thaw Bayesian Optimization

Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning

Universal Language Model Fine-tuning for Text Classification

Feature-Critic Networks for Heterogeneous Domain Generalization

Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer

Complexity of Linear Regions in Deep Networks

Broadband DOA estimation using Convolutional neural networks trained with noise signals

Understanding Probabilistic Sparse Gaussian Process Approximations

End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances

Neural Jump Stochastic Differential Equations

Bike Flow Prediction with Multi-Graph Convolutional Networks

Spurious Local Minima are Common in Two-Layer ReLU Neural Networks

Adaptive Aggregation Networks for Class-Incremental Learning

Inductive Matrix Completion Based on Graph Neural Networks

Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learning

What Can Neural Networks Reason About?

Benchmarking Simulation-Based Inference

Adversarial Examples that Fool both Computer Vision and Time-Limited Humans

EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals

Differentiable Causal Discovery from Interventional Data