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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4,501 to 4,560 of 6,779

Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation
Cong Liao, Haoti Zhong, Anna Squicciarini +2
cs.CRcs.LGstat.MLarXiv:1808.10307v12018
Constructing Unrestricted Adversarial Examples with Generative Models
Yang Song, Rui Shu, Nate Kushman +1
cs.LGcs.AIcs.CRarXiv:1805.07894v42018
Alzheimer's Dementia Recognition through Spontaneous Speech: The ADReSS Challenge
Saturnino Luz, Fasih Haider, Sofia de la Fuente +2
eess.AScs.LGstat.MLarXiv:2004.06833v32020
Cooperative Perception for 3D Object Detection in Driving Scenarios using Infrastructure Sensors
Eduardo Arnold, Mehrdad Dianati, Robert de Temple +1
cs.CVcs.LGcs.MAarXiv:1912.12147v22019
Combating Fake News: A Survey on Identification and Mitigation Techniques
Karishma Sharma, Feng Qian, He Jiang +3
cs.LGcs.AIcs.SIarXiv:1901.06437v12019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
Umut Simsekli, Levent Sagun, Mert Gurbuzbalaban
cs.LGstat.MLarXiv:1901.06053v12019
Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization
Hesham Mostafa, Xin Wang
cs.LGstat.MLarXiv:1902.05967v32019
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches
Yeming Wen, Paul Vicol, Jimmy Ba +2
cs.LGstat.MLarXiv:1803.04386v22018
Domain Generalization by Marginal Transfer Learning
Gilles Blanchard, Aniket Anand Deshmukh, Urun Dogan +2
stat.MLarXiv:1711.07910v32017
BAGAN: Data Augmentation with Balancing GAN
Giovanni Mariani, Florian Scheidegger, Roxana Istrate +2
cs.CVcs.LGstat.MLarXiv:1803.09655v22018
Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret
Animashree Anandkumar, Nithin Michael, Ao Kevin Tang +1
cs.NIstat.MLarXiv:1006.1673v12010
A mathematical theory of semantic development in deep neural networks
Andrew M. Saxe, James L. McClelland, Surya Ganguli
cs.LGcs.AIq-bio.NCarXiv:1810.10531v12018
Self-attention for raw optical Satellite Time Series Classification
Marc Rußwurm, Marco Körner
cs.LGeess.IVstat.MLarXiv:1910.10536v32019
i-RevNet: Deep Invertible Networks
Jörn-Henrik Jacobsen, Arnold Smeulders, Edouard Oyallon
cs.LGcs.CVstat.MLarXiv:1802.07088v12018
A Survey of Available Corpora for Building Data-Driven Dialogue Systems
Iulian Vlad Serban, Ryan Lowe, Peter Henderson +2
cs.CLcs.AIcs.HCarXiv:1512.05742v32015
Self-supervised ECG Representation Learning for Emotion Recognition
Pritam Sarkar, Ali Etemad
eess.SPcs.LGstat.MLarXiv:2002.03898v22020
Understanding and Improving Fast Adversarial Training
Maksym Andriushchenko, Nicolas Flammarion
cs.LGcs.CRcs.CVarXiv:2007.02617v22020
Proximal Methods for Hierarchical Sparse Coding
Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski +1
stat.MLarXiv:1009.2139v42010
Random Forests for Big Data
Robin Genuer, Jean-Michel Poggi, Christine Tuleau-Malot +1
stat.MLcs.LGmath.STarXiv:1511.08327v22015
BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning
Abhijit Guha Roy, Shayan Siddiqui, Sebastian Pölsterl +2
cs.LGstat.MLarXiv:1905.06731v12019
Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting
Weiqi Chen, Ling Chen, Yu Xie +3
cs.LGstat.MLarXiv:1911.12093v12019
Frequency Recognition in SSVEP-based BCI using Multiset Canonical Correlation Analysis
Yu Zhang, Guoxu Zhou, Jing Jin +2
stat.MLarXiv:1308.5609v22013
DeepMDP: Learning Continuous Latent Space Models for Representation Learning
Carles Gelada, Saurabh Kumar, Jacob Buckman +2
cs.LGstat.MLarXiv:1906.02736v12019
Riemannian Adaptive Optimization Methods
Gary Bécigneul, Octavian-Eugen Ganea
cs.LGstat.MLarXiv:1810.00760v22018
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms
Jianyu Wang, Gauri Joshi
cs.LGcs.DCstat.MLarXiv:1808.07576v32018
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity
Amit Daniely, Roy Frostig, Yoram Singer
cs.LGcs.AIcs.CCarXiv:1602.05897v22016
Outer Product-based Neural Collaborative Filtering
Xiangnan He, Xiaoyu Du, Xiang Wang +3
cs.IRcs.LGstat.MLarXiv:1808.03912v12018
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation
Cong Xie, Sanmi Koyejo, Indranil Gupta
cs.LGcs.CRcs.DCarXiv:1903.03936v12019
Differentially Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds
Raef Bassily, Adam Smith, Abhradeep Thakurta
cs.LGcs.CRstat.MLarXiv:1405.7085v22014
Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild
Abubakar Abid, Ali Abdalla, Ali Abid +3
cs.LGcs.HCstat.MLarXiv:1906.02569v12019
Hierarchical Variational Models
Rajesh Ranganath, Dustin Tran, David M. Blei
stat.MLcs.LGstat.COarXiv:1511.02386v22015
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches
Kacper Sokol, Peter Flach
cs.LGcs.AIstat.MLarXiv:1912.05100v12019
Communication-Efficient Distributed Dual Coordinate Ascent
Martin Jaggi, Virginia Smith, Martin Takáč +4
cs.LGmath.OCstat.MLarXiv:1409.1458v22014
An Overview of Deep Semi-Supervised Learning
Yassine Ouali, Céline Hudelot, Myriam Tami
cs.LGstat.MLarXiv:2006.05278v22020
Are Labels Required for Improving Adversarial Robustness?
Jonathan Uesato, Jean-Baptiste Alayrac, Po-Sen Huang +3
cs.LGcs.CVstat.MLarXiv:1905.13725v42019
On the importance of single directions for generalization
Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz +1
stat.MLcs.AIcs.LGarXiv:1803.06959v42018
MetNet: A Neural Weather Model for Precipitation Forecasting
Casper Kaae Sønderby, Lasse Espeholt, Jonathan Heek +6
cs.LGphysics.ao-phstat.MLarXiv:2003.12140v22020
Accurate estimation of influenza epidemics using Google search data via ARGO
Shihao Yang, Mauricio Santillana, S. C. Kou
stat.APcs.SIstat.MLarXiv:1505.00864v22015
Multi-task Deep Reinforcement Learning with PopArt
Matteo Hessel, Hubert Soyer, Lasse Espeholt +3
cs.LGstat.MLarXiv:1809.04474v12018
MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks
Ariel Gordon, Elad Eban, Ofir Nachum +4
cs.LGstat.MLarXiv:1711.06798v32017
Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search
Xiangxiang Chu, Tianbao Zhou, Bo Zhang +1
cs.LGcs.AIcs.CVarXiv:1911.12126v42019
Hyperbolic Entailment Cones for Learning Hierarchical Embeddings
Octavian-Eugen Ganea, Gary Bécigneul, Thomas Hofmann
cs.LGstat.MLarXiv:1804.01882v32018
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
Kartik Ahuja, Ethan Caballero, Dinghuai Zhang +4
cs.LGstat.MLarXiv:2106.06607v22021
Adversarial Feature Matching for Text Generation
Yizhe Zhang, Zhe Gan, Kai Fan +4
stat.MLcs.CLcs.LGarXiv:1706.03850v32017
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation
Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda +1
cs.LGcs.CVstat.MLarXiv:2005.01807v12020
Structured Sparse Principal Component Analysis
Rodolphe Jenatton, Guillaume Obozinski, Francis Bach
stat.MLarXiv:0909.1440v12009
GFlowNet Foundations
Yoshua Bengio, Salem Lahlou, Tristan Deleu +3
cs.LGcs.AIstat.MLarXiv:2111.09266v52021
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov +1
stat.MLcs.LGarXiv:2002.06470v42020
Never Give Up: Learning Directed Exploration Strategies
Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi +8
cs.LGstat.MLarXiv:2002.06038v12020
Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations
Christian Beck, Weinan E, Arnulf Jentzen
math.NAcs.LGcs.NEarXiv:1709.05963v12017
Traversing Knowledge Graphs in Vector Space
Kelvin Guu, John Miller, Percy Liang
cs.CLcs.AIcs.DBarXiv:1506.01094v22015
Learning to Compose Domain-Specific Transformations for Data Augmentation
Alexander J. Ratner, Henry R. Ehrenberg, Zeshan Hussain +2
stat.MLcs.CVcs.LGarXiv:1709.01643v32017
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations
Jiaheng Wei, Zhaowei Zhu, Hao Cheng +3
cs.LGstat.MLarXiv:2110.12088v22021
Graph Convolutional Networks with EigenPooling
Yao Ma, Suhang Wang, Charu C. Aggarwal +1
cs.LGstat.MLarXiv:1904.13107v22019
Universal features of price formation in financial markets: perspectives from Deep Learning
Justin Sirignano, Rama Cont
q-fin.STq-fin.TRstat.MLarXiv:1803.06917v12018
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson
stat.MLcs.LGarXiv:2006.08545v12020
Thoracic Disease Identification and Localization with Limited Supervision
Zhe Li, Chong Wang, Mei Han +4
cs.CVstat.MLarXiv:1711.06373v62017
Gradient-Based Neural DAG Learning
Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu +1
cs.LGstat.MLarXiv:1906.02226v22019
Understanding and mitigating gradient pathologies in physics-informed neural networks
Sifan Wang, Yujun Teng, Paris Perdikaris
cs.LGmath.NAstat.MLarXiv:2001.04536v12020
Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks
Yanbang Wang, Yen-Yu Chang, Yunyu Liu +2
cs.LGcs.SIstat.MLarXiv:2101.05974v52021

Machine Learning (stat)

Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation

Constructing Unrestricted Adversarial Examples with Generative Models

Alzheimer's Dementia Recognition through Spontaneous Speech: The ADReSS Challenge

Cooperative Perception for 3D Object Detection in Driving Scenarios using Infrastructure Sensors

Combating Fake News: A Survey on Identification and Mitigation Techniques

A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks

Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization

Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches

Domain Generalization by Marginal Transfer Learning

BAGAN: Data Augmentation with Balancing GAN

Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret

A mathematical theory of semantic development in deep neural networks

Self-attention for raw optical Satellite Time Series Classification

i-RevNet: Deep Invertible Networks

A Survey of Available Corpora for Building Data-Driven Dialogue Systems

Self-supervised ECG Representation Learning for Emotion Recognition

Understanding and Improving Fast Adversarial Training

Proximal Methods for Hierarchical Sparse Coding

Random Forests for Big Data

BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning

Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting

Frequency Recognition in SSVEP-based BCI using Multiset Canonical Correlation Analysis

DeepMDP: Learning Continuous Latent Space Models for Representation Learning

Riemannian Adaptive Optimization Methods

Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms

Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity

Outer Product-based Neural Collaborative Filtering

Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation

Differentially Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds

Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild

Hierarchical Variational Models

Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches

Communication-Efficient Distributed Dual Coordinate Ascent

An Overview of Deep Semi-Supervised Learning

Are Labels Required for Improving Adversarial Robustness?

On the importance of single directions for generalization

MetNet: A Neural Weather Model for Precipitation Forecasting

Accurate estimation of influenza epidemics using Google search data via ARGO

Multi-task Deep Reinforcement Learning with PopArt

MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks

Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search

Hyperbolic Entailment Cones for Learning Hierarchical Embeddings

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization

Adversarial Feature Matching for Text Generation

Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation

Structured Sparse Principal Component Analysis

GFlowNet Foundations

Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning

Never Give Up: Learning Directed Exploration Strategies

Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations

Traversing Knowledge Graphs in Vector Space

Learning to Compose Domain-Specific Transformations for Data Augmentation

Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations

Graph Convolutional Networks with EigenPooling

Universal features of price formation in financial markets: perspectives from Deep Learning

Why Normalizing Flows Fail to Detect Out-of-Distribution Data

Thoracic Disease Identification and Localization with Limited Supervision

Gradient-Based Neural DAG Learning

Understanding and mitigating gradient pathologies in physics-informed neural networks

Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks