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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3,421 to 3,480 of 6,782

On the Theory of Transfer Learning: The Importance of Task Diversity
Nilesh Tripuraneni, Michael I. Jordan, Chi Jin
cs.LGstat.MLarXiv:2006.11650v22020
Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation
Risto Vuorio, Shao-Hua Sun, Hexiang Hu +1
cs.LGcs.AIstat.MLarXiv:1910.13616v12019
Adaptive Conformal Predictions for Time Series
Margaux Zaffran, Aymeric Dieuleveut, Olivier Féron +2
stat.MLcs.LGarXiv:2202.07282v12022
An ensemble-based system for automatic screening of diabetic retinopathy
Balint Antal, Andras Hajdu
cs.CVcs.LGstat.AParXiv:1410.8576v12014
Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-tuning
Weifeng Ge, Yizhou Yu
cs.CVcs.AIcs.LGarXiv:1702.08690v22017
Adversarial Regularizers in Inverse Problems
Sebastian Lunz, Ozan Öktem, Carola-Bibiane Schönlieb
cs.CVcs.LGmath.NAarXiv:1805.11572v22018
A Scalable Discrete-Time Survival Model for Neural Networks
Michael F. Gensheimer, Balasubramanian Narasimhan
stat.MLcs.CYcs.LGarXiv:1805.00917v32018
Unsupervised Single Image Dehazing Using Dark Channel Prior Loss
Alona Golts, Daniel Freedman, Michael Elad
cs.CVcs.LGstat.MLarXiv:1812.07051v22018
A Cost-Sensitive Deep Belief Network for Imbalanced Classification
Chong Zhang, Kay Chen Tan, Haizhou Li +1
cs.LGstat.MLarXiv:1804.10801v22018
Structured Transforms for Small-Footprint Deep Learning
Vikas Sindhwani, Tara N. Sainath, Sanjiv Kumar
stat.MLcs.CVcs.LGarXiv:1510.01722v12015
Explainable Deep One-Class Classification
Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen +3
cs.CVcs.LGstat.MLarXiv:2007.01760v32020
Measure Contribution of Participants in Federated Learning
Guan Wang, Charlie Xiaoqian Dang, Ziye Zhou
cs.LGstat.MLarXiv:1909.08525v12019
Learning Stable Deep Dynamics Models
Gaurav Manek, J. Zico Kolter
cs.LGmath.DSstat.MLarXiv:2001.06116v12020
Provably efficient RL with Rich Observations via Latent State Decoding
Simon S. Du, Akshay Krishnamurthy, Nan Jiang +3
cs.LGstat.MLarXiv:1901.09018v32019
Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network
Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
cs.CVcs.HCcs.LGarXiv:1910.11111v32019
Anomaly Detection with Density Estimation
Benjamin Nachman, David Shih
hep-phhep-exphysics.data-anarXiv:2001.04990v22020
Planning with Goal-Conditioned Policies
Soroush Nasiriany, Vitchyr H. Pong, Steven Lin +1
cs.LGcs.AIcs.ROarXiv:1911.08453v12019
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Kimin Lee, Michael Laskin, Aravind Srinivas +1
cs.LGcs.AIstat.MLarXiv:2007.04938v42020
Joint Multimodal Learning with Deep Generative Models
Masahiro Suzuki, Kotaro Nakayama, Yutaka Matsuo
stat.MLcs.LGarXiv:1611.01891v12016
Self-Adaptive Training: beyond Empirical Risk Minimization
Lang Huang, Chao Zhang, Hongyang Zhang
cs.LGcs.CVstat.MLarXiv:2002.10319v22020
Deep Learning with Gaussian Differential Privacy
Zhiqi Bu, Jinshuo Dong, Qi Long +1
cs.LGcs.CRstat.MLarXiv:1911.11607v32019
Bayesian Models of Graphs, Arrays and Other Exchangeable Random Structures
Peter Orbanz, Daniel M. Roy
math.STstat.MLarXiv:1312.7857v22013
Inherent Tradeoffs in Learning Fair Representations
Han Zhao, Geoffrey J. Gordon
cs.LGcs.AIstat.MLarXiv:1906.08386v62019
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group
Mario Lezcano-Casado, David Martínez-Rubio
cs.LGstat.MLarXiv:1901.08428v32019
A Universal Law of Robustness via Isoperimetry
Sébastien Bubeck, Mark Sellke
cs.LGstat.MLarXiv:2105.12806v42021
PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures
Mathieu Carrière, Frédéric Chazal, Yuichi Ike +3
stat.MLcs.CGcs.LGarXiv:1904.09378v42019
IPO: Interior-point Policy Optimization under Constraints
Yongshuai Liu, Jiaxin Ding, Xin Liu
cs.LGmath.OCstat.MLarXiv:1910.09615v12019
Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review
Marjane Khodatars, Afshin Shoeibi, Delaram Sadeghi +12
cs.LGeess.IVstat.MLarXiv:2007.01285v42020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
cs.LGstat.MLarXiv:2006.09239v22020
Adaptive Neural Signal Detection for Massive MIMO
Mehrdad Khani, Mohammad Alizadeh, Jakob Hoydis +1
eess.SPcs.LGstat.MLarXiv:1906.04610v12019
Contextualized Spatial-Temporal Network for Taxi Origin-Destination Demand Prediction
Lingbo Liu, Zhilin Qiu, Guanbin Li +3
cs.LGcs.AIstat.MLarXiv:1905.06335v12019
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai, Shengjie Luo, Keyulu Xu +3
cs.LGmath.OCstat.MLarXiv:2009.03294v32020
Dissecting Neural ODEs
Stefano Massaroli, Michael Poli, Jinkyoo Park +2
cs.LGcs.NEstat.MLarXiv:2002.08071v42020
Discovering Causal Signals in Images
David Lopez-Paz, Robert Nishihara, Soumith Chintala +2
stat.MLcs.CVarXiv:1605.08179v22016
Time Varying Undirected Graphs
Shuheng Zhou, John Lafferty, Larry Wasserman
stat.MLmath.STarXiv:0802.2758v42008
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
Francis Bach
cs.LGstat.MLarXiv:0809.1493v12008
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization
Shicong Cen, Chen Cheng, Yuxin Chen +2
stat.MLcs.ITcs.LGarXiv:2007.06558v52020
An Online Convex Optimization Approach to Dynamic Network Resource Allocation
Tianyi Chen, Qing Ling, Georgios B. Giannakis
eess.SYcs.LGmath.OCarXiv:1701.03974v22017
CycleGAN, a Master of Steganography
Casey Chu, Andrey Zhmoginov, Mark Sandler
cs.CVcs.LGstat.MLarXiv:1712.02950v22017
Beta-Negative Binomial Process and Poisson Factor Analysis
Mingyuan Zhou, Lauren Hannah, David Dunson +1
stat.MLstat.MEarXiv:1112.3605v42011
Composable Deep Reinforcement Learning for Robotic Manipulation
Tuomas Haarnoja, Vitchyr Pong, Aurick Zhou +3
cs.LGcs.AIcs.ROarXiv:1803.06773v12018
Learning between the peaks: sharp asymptotics for kernel ridge regression under power-law anisotropy
Lorenzo Rizzi, Arie Wortsman Zurich, Bruno Loureiro
stat.MLcs.LGarXiv:2608.28564v12026
Understanding the Limitations of Variational Mutual Information Estimators
Jiaming Song, Stefano Ermon
cs.LGcs.ITstat.MLarXiv:1910.06222v22019
Visual Analytics for Explainable Deep Learning
Jaegul Choo, Shixia Liu
cs.HCcs.LGstat.MLarXiv:1804.02527v12018
Foundations of data imbalance and solutions for a data democracy
Ajay Kulkarni, Deri Chong, Feras A. Batarseh
cs.LGcs.AIstat.MLarXiv:2108.00071v12021
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi
cs.LGstat.MLarXiv:2003.12815v22020
ResNet with one-neuron hidden layers is a Universal Approximator
Hongzhou Lin, Stefanie Jegelka
cs.LGstat.MLarXiv:1806.10909v22018
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction
Yaodong Yu, Kwan Ho Ryan Chan, Chong You +2
cs.LGcs.CVcs.ITarXiv:2006.08558v12020
Explaining the Unique Nature of Individual Gait Patterns with Deep Learning
Fabian Horst, Sebastian Lapuschkin, Wojciech Samek +2
cs.LGstat.MLarXiv:1808.04308v22018
Local Graph Clustering with Network Lasso
Alexander Jung, Yasmin SarcheshmehPour
cs.LGstat.MLarXiv:2004.12199v32020
Generalized Splines and Gaussian Processes
Michael Unser
math.STcs.LGmath.FAarXiv:2608.28446v12026
Off-policy evaluation for slate recommendation
Adith Swaminathan, Akshay Krishnamurthy, Alekh Agarwal +4
cs.LGcs.AIstat.MLarXiv:1605.04812v32016
When Does Self-Supervision Help Graph Convolutional Networks?
Yuning You, Tianlong Chen, Zhangyang Wang +1
cs.LGstat.MLarXiv:2006.09136v42020
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Zi Wang, Clement Gehring, Pushmeet Kohli +1
stat.MLcs.LGmath.OCarXiv:1706.01445v42017
Towards Conceptual Compression
Karol Gregor, Frederic Besse, Danilo Jimenez Rezende +2
stat.MLcs.CVcs.LGarXiv:1604.08772v12016
Fast global convergence of gradient methods for high-dimensional statistical recovery
Alekh Agarwal, Sahand N. Negahban, Martin J. Wainwright
stat.MLcs.ITarXiv:1104.4824v32011
Detecting change points in the large-scale structure of evolving networks
Leto Peel, Aaron Clauset
cs.SIphysics.soc-phstat.MLarXiv:1403.0989v22014
Localizing Global Discrepancies: Marginal Contributions and Contextual Anomaly Detection
Tommaso dorigo
stat.MLcs.LGphysics.data-anarXiv:2608.28375v12026
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
Ari S. Morcos, Haonan Yu, Michela Paganini +1
stat.MLcs.LGcs.NEarXiv:1906.02773v22019
Adversarial Training Can Hurt Generalization
Aditi Raghunathan, Sang Michael Xie, Fanny Yang +2
cs.LGstat.MLarXiv:1906.06032v22019

Machine Learning (stat)

On the Theory of Transfer Learning: The Importance of Task Diversity

Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation

Adaptive Conformal Predictions for Time Series

An ensemble-based system for automatic screening of diabetic retinopathy

Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-tuning

Adversarial Regularizers in Inverse Problems

A Scalable Discrete-Time Survival Model for Neural Networks

Unsupervised Single Image Dehazing Using Dark Channel Prior Loss

A Cost-Sensitive Deep Belief Network for Imbalanced Classification

Structured Transforms for Small-Footprint Deep Learning

Explainable Deep One-Class Classification

Measure Contribution of Participants in Federated Learning

Learning Stable Deep Dynamics Models

Provably efficient RL with Rich Observations via Latent State Decoding

Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network

Anomaly Detection with Density Estimation

Planning with Goal-Conditioned Policies

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning

Joint Multimodal Learning with Deep Generative Models

Self-Adaptive Training: beyond Empirical Risk Minimization

Deep Learning with Gaussian Differential Privacy

Bayesian Models of Graphs, Arrays and Other Exchangeable Random Structures

Inherent Tradeoffs in Learning Fair Representations

Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group

A Universal Law of Robustness via Isoperimetry

PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures

IPO: Interior-point Policy Optimization under Constraints

Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review

Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts

Adaptive Neural Signal Detection for Massive MIMO

Contextualized Spatial-Temporal Network for Taxi Origin-Destination Demand Prediction

GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training

Dissecting Neural ODEs

Discovering Causal Signals in Images

Time Varying Undirected Graphs

Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning

Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization

An Online Convex Optimization Approach to Dynamic Network Resource Allocation

CycleGAN, a Master of Steganography

Beta-Negative Binomial Process and Poisson Factor Analysis

Composable Deep Reinforcement Learning for Robotic Manipulation

Learning between the peaks: sharp asymptotics for kernel ridge regression under power-law anisotropy

Understanding the Limitations of Variational Mutual Information Estimators

Visual Analytics for Explainable Deep Learning

Foundations of data imbalance and solutions for a data democracy

Efficient Domain Generalization via Common-Specific Low-Rank Decomposition

ResNet with one-neuron hidden layers is a Universal Approximator

Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction

Explaining the Unique Nature of Individual Gait Patterns with Deep Learning

Local Graph Clustering with Network Lasso

Generalized Splines and Gaussian Processes

Off-policy evaluation for slate recommendation

When Does Self-Supervision Help Graph Convolutional Networks?

Batched Large-scale Bayesian Optimization in High-dimensional Spaces

Towards Conceptual Compression

Fast global convergence of gradient methods for high-dimensional statistical recovery

Detecting change points in the large-scale structure of evolving networks

Localizing Global Discrepancies: Marginal Contributions and Contextual Anomaly Detection

One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers

Adversarial Training Can Hurt Generalization