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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7,081 to 7,140 of 9,716

A Direct Estimation of High Dimensional Stationary Vector Autoregressions
Fang Han, Huanran Lu, Han Liu
stat.MLarXiv:1307.0293v32013
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking
Michael Sejr Schlichtkrull, Nicola De Cao, Ivan Titov
cs.CLcs.LGstat.MLarXiv:2010.00577v32020
Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
Cem Anil, Ashwini Pokle, Kaiqu Liang +5
cs.LGstat.MLarXiv:2211.09961v12022
Machine Learning with Membership Privacy using Adversarial Regularization
Milad Nasr, Reza Shokri, Amir Houmansadr
stat.MLcs.CRcs.LGarXiv:1807.05852v12018
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
Dan Hendrycks, Mantas Mazeika, Saurav Kadavath +1
cs.LGcs.CVstat.MLarXiv:1906.12340v22019
GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
Marc Brockschmidt
cs.LGstat.MLarXiv:1906.12192v52019
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
Nikolaus Hansen, Anne Auger, Raymond Ros +3
cs.AIcs.MSmath.NAarXiv:1603.08785v42016
Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation
Diederik P. Kingma, Ruiqi Gao
cs.LGcs.AIstat.MLarXiv:2303.00848v72023
Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL
Anusha Nagabandi, Chelsea Finn, Sergey Levine
cs.LGcs.AIcs.ROarXiv:1812.07671v22018
Regularized Spectral Clustering under the Degree-Corrected Stochastic Blockmodel
Tai Qin, Karl Rohe
stat.MLcs.LGmath.STarXiv:1309.4111v12013
Risk and parameter convergence of logistic regression
Ziwei Ji, Matus Telgarsky
cs.LGmath.OCstat.MLarXiv:1803.07300v32018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers
Zeyuan Allen-Zhu, Yuanzhi Li, Yingyu Liang
cs.LGcs.DScs.NEarXiv:1811.04918v62018
Conformal Prediction: a Unified Review of Theory and New Challenges
Matteo Fontana, Gianluca Zeni, Simone Vantini
cs.LGecon.EMstat.MEarXiv:2005.07972v22020
An Empirical Survey of Data Augmentation for Time Series Classification with Neural Networks
Brian Kenji Iwana, Seiichi Uchida
cs.LGstat.MLarXiv:2007.15951v42020
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control
Sai Qian Zhang, Qi Zhang, Jieyu Lin
cs.LGstat.MLarXiv:1909.02682v22019
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference
Klas Leino, Matt Fredrikson
cs.LGcs.CRstat.MLarXiv:1906.11798v22019
DsDm: Model-Aware Dataset Selection with Datamodels
Logan Engstrom, Axel Feldmann, Aleksander Madry
cs.LGstat.MLarXiv:2401.12926v12024
Generalized Inner Loop Meta-Learning
Edward Grefenstette, Brandon Amos, Denis Yarats +6
cs.LGstat.MLarXiv:1910.01727v22019
Nonlinear Information Bottleneck
Artemy Kolchinsky, Brendan D. Tracey, David H. Wolpert
cs.ITcs.LGstat.MLarXiv:1705.02436v92017
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy
Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin +6
cs.LGcs.CRstat.MLarXiv:2303.00654v32023
DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles
Huanrui Yang, Jingyang Zhang, Hongliang Dong +6
cs.LGcs.CRstat.MLarXiv:2009.14720v22020
Forecasting Transportation Network Speed Using Deep Capsule Networks with Nested LSTM Models
Xiaolei Ma, Yi Li, Zhiyong Cui +1
cs.LGstat.MLarXiv:1811.04745v12018
Deep learning cardiac motion analysis for human survival prediction
Ghalib A. Bello, Timothy J. W. Dawes, Jinming Duan +8
cs.LGcs.CVstat.MLarXiv:1810.03382v12018
Differentiable Systematic Resampling for Variational Sequential Monte Carlo
Fredrik Cumlin, Saikat Chatterjee
stat.MLcs.LGeess.SParXiv:2610.12094v12026
TopRank: A practical algorithm for online stochastic ranking
Tor Lattimore, Branislav Kveton, Shuai Li +1
stat.MLcs.LGarXiv:1806.02248v22018
Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge
Ryan J. Gallagher, Kyle Reing, David Kale +1
cs.CLcs.IRcs.ITarXiv:1611.10277v42016
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen +17
cs.AIcs.CVcs.HCarXiv:1909.03012v22019
Weisfeiler and Lehman Go Cellular: CW Networks
Cristian Bodnar, Fabrizio Frasca, Nina Otter +4
cs.LGstat.MLarXiv:2106.12575v32021
Towards Scaling Reinforcement Learning to Massive Populations: Learning Mean-Field Representations
Aditya Makkar, Benjamin Unger, Jeongyeol Kwon +3
cs.MAcs.LGstat.MLarXiv:2609.02928v12026
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks
Yu Bai, Jason D. Lee
cs.LGmath.OCstat.MLarXiv:1910.01619v22019
An Overview of Robust Subspace Recovery
Gilad Lerman, Tyler Maunu
cs.LGstat.MLarXiv:1803.01013v22018
Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs
Lior Shani, Yonathan Efroni, Shie Mannor
cs.LGmath.OCstat.MLarXiv:1909.02769v22019
An ADMM Algorithm for a Class of Total Variation Regularized Estimation Problems
Bo Wahlberg, Stephen Boyd, Mariette Annergren +1
stat.MLarXiv:1203.1828v12012
Decentralized Computation Offloading for Multi-User Mobile Edge Computing: A Deep Reinforcement Learning Approach
Zhao Chen, Xiaodong Wang
cs.LGeess.SPmath.OCarXiv:1812.07394v12018
Tuned Models of Peer Assessment in MOOCs
Chris Piech, Jonathan Huang, Zhenghao Chen +3
cs.LGcs.AIcs.HCarXiv:1307.2579v12013
Representation Learning via Invariant Causal Mechanisms
Jovana Mitrovic, Brian McWilliams, Jacob Walker +2
cs.LGcs.CVstat.MLarXiv:2010.07922v12020
Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squares Minimization
Canyi Lu, Zhouchen Lin, Shuicheng Yan
cs.LGcs.CVstat.MLarXiv:1401.7413v22014
Stochastic bandits robust to adversarial corruptions
Thodoris Lykouris, Vahab Mirrokni, Renato Paes Leme
cs.LGcs.DScs.GTarXiv:1803.09353v12018
Path-conditioned training: a principled way to rescale ReLU neural networks
Arthur Lebeurrier, Titouan Vayer, Rémi Gribonval
stat.MLcs.LGmath.OCarXiv:2602.19799v22026
Unsupervised Predictive Memory in a Goal-Directed Agent
Greg Wayne, Chia-Chun Hung, David Amos +21
cs.LGstat.MLarXiv:1803.10760v12018
Modeling Events with Cascades of Poisson Processes
Aleksandr Simma, Michael I. Jordan
cs.LGcs.AIstat.MLarXiv:1203.3516v12012
ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases
Stéphane d'Ascoli, Hugo Touvron, Matthew Leavitt +3
cs.CVcs.LGstat.MLarXiv:2103.10697v22021
Transfer Learning for Motor Imagery Based Brain-Computer Interfaces: A Complete Pipeline
Dongrui Wu, Xue Jiang, Ruimin Peng +3
eess.SPcs.HCcs.LGarXiv:2007.03746v32020
Global optimization of Lipschitz functions
Cédric Malherbe, Nicolas Vayatis
stat.MLarXiv:1703.02628v32017
Meta-Learning: A Survey
Joaquin Vanschoren
cs.LGstat.MLarXiv:1810.03548v12018
Convergence Rates of Variational Posterior Distributions
Fengshuo Zhang, Chao Gao
math.STstat.MLstat.THarXiv:1712.02519v42017
SLICE: Sequential Likelihood-Free Inference via Conformal E-Values
Stefano Cortinovis, Laura Battaglia, François Caron
stat.MEstat.MLarXiv:2610.13855v12026
Interpretable Classification Models for Recidivism Prediction
Jiaming Zeng, Berk Ustun, Cynthia Rudin
stat.MLstat.AParXiv:1503.07810v62015
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
Yizhen Wang, Somesh Jha, Kamalika Chaudhuri
stat.MLcs.CRcs.LGarXiv:1706.03922v62017
Personalized Federated Learning with Moreau Envelopes
Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen
cs.LGcs.DCstat.MLarXiv:2006.08848v32020
Crafting Adversarial Examples For Speech Paralinguistics Applications
Yuan Gong, Christian Poellabauer
cs.LGcs.CRcs.SDarXiv:1711.03280v22017
RoPE attention is an exact forward-pass gradient step with softmax intact
Julie Huang, Maggie Chlon, Leon Chlon
stat.MLcs.LGarXiv:2609.06685v12026
Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations
Frank Po-Chen Lin, Seyyedali Hosseinalipour, Sheikh Shams Azam +2
cs.LGcs.DCstat.MLarXiv:2103.10481v32021
Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values
Julius Adebayo, Justin Gilmer, Ian Goodfellow +1
cs.CVcs.LGstat.MLarXiv:1810.03307v12018
Q-learning with Adjoint Matching
Qiyang Li, Sergey Levine
cs.LGcs.AIcs.ROarXiv:2601.14234v42026
Estimating Mixture Entropy with Pairwise Distances
Artemy Kolchinsky, Brendan D. Tracey
cs.ITmath.ITstat.MEarXiv:1706.02419v42017
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control
Masatoshi Uehara, Yulai Zhao, Kevin Black +6
cs.LGcs.AIstat.MLarXiv:2402.15194v22024
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects
Adam R. Kosiorek, Hyunjik Kim, Ingmar Posner +1
cs.LGcs.CVstat.MLarXiv:1806.01794v22018
Learning Generative Models with Sinkhorn Divergences
Aude Genevay, Gabriel Peyré, Marco Cuturi
stat.MLarXiv:1706.00292v32017
How to learn a graph from smooth signals
Vassilis Kalofolias
stat.MLcs.LGphysics.data-anarXiv:1601.02513v12016

Machine Learning (stat)

A Direct Estimation of High Dimensional Stationary Vector Autoregressions

Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking

Path Independent Equilibrium Models Can Better Exploit Test-Time Computation

Machine Learning with Membership Privacy using Adversarial Regularization

Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty

GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation

COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting

Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation

Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL

Regularized Spectral Clustering under the Degree-Corrected Stochastic Blockmodel

Risk and parameter convergence of logistic regression

Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers

Conformal Prediction: a Unified Review of Theory and New Challenges

An Empirical Survey of Data Augmentation for Time Series Classification with Neural Networks

Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control

Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference

DsDm: Model-Aware Dataset Selection with Datamodels

Generalized Inner Loop Meta-Learning

Nonlinear Information Bottleneck

How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy

DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles

Forecasting Transportation Network Speed Using Deep Capsule Networks with Nested LSTM Models

Deep learning cardiac motion analysis for human survival prediction

Differentiable Systematic Resampling for Variational Sequential Monte Carlo

TopRank: A practical algorithm for online stochastic ranking

Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

Weisfeiler and Lehman Go Cellular: CW Networks

Towards Scaling Reinforcement Learning to Massive Populations: Learning Mean-Field Representations

Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks

An Overview of Robust Subspace Recovery

Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs

An ADMM Algorithm for a Class of Total Variation Regularized Estimation Problems

Decentralized Computation Offloading for Multi-User Mobile Edge Computing: A Deep Reinforcement Learning Approach

Tuned Models of Peer Assessment in MOOCs

Representation Learning via Invariant Causal Mechanisms

Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squares Minimization

Stochastic bandits robust to adversarial corruptions

Path-conditioned training: a principled way to rescale ReLU neural networks

Unsupervised Predictive Memory in a Goal-Directed Agent

Modeling Events with Cascades of Poisson Processes

ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases

Transfer Learning for Motor Imagery Based Brain-Computer Interfaces: A Complete Pipeline

Global optimization of Lipschitz functions

Meta-Learning: A Survey

Convergence Rates of Variational Posterior Distributions

SLICE: Sequential Likelihood-Free Inference via Conformal E-Values

Interpretable Classification Models for Recidivism Prediction

Analyzing the Robustness of Nearest Neighbors to Adversarial Examples

Personalized Federated Learning with Moreau Envelopes

Crafting Adversarial Examples For Speech Paralinguistics Applications

RoPE attention is an exact forward-pass gradient step with softmax intact

Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations

Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values

Q-learning with Adjoint Matching

Estimating Mixture Entropy with Pairwise Distances

Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control

Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects

Learning Generative Models with Sinkhorn Divergences

How to learn a graph from smooth signals