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.

Search paper metadata (including unsummarized papers)

7,501 to 7,560 of 9,654

Continual Learning in Generative Adversarial Nets
Ari Seff, Alex Beatson, Daniel Suo +1
cs.LGcs.AIstat.MLarXiv:1705.08395v12017
Sparsifying Stochasticity, Not Capacity: Partial Stochasticity via Deep Weight Factorization of Prior Scales
Marius P Linhard, Maurizio Filippone
stat.MLcs.LGarXiv:2610.09886v12026
Nonlinear Interference Mitigation via Deep Neural Networks
Christian Häger, Henry D. Pfister
cs.ITstat.MLarXiv:1710.06234v12017
Deep reinforcement learning from human preferences
Paul Christiano, Jan Leike, Tom B. Brown +3
stat.MLcs.AIcs.HCarXiv:1706.03741v42017
Robust Kernel Density Estimation
JooSeuk Kim, Clayton D. Scott
stat.MLcs.LGstat.MEarXiv:1107.3133v22011
Flow Matching on General Geometries
Ricky T. Q. Chen, Yaron Lipman
cs.LGcs.AIstat.MLarXiv:2302.03660v32023
Model-Based Reinforcement Learning via Meta-Policy Optimization
Ignasi Clavera, Jonas Rothfuss, John Schulman +3
cs.LGcs.AIstat.MLarXiv:1809.05214v12018
The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes
Nicholas Heller, Niranjan Sathianathen, Arveen Kalapara +17
q-bio.QMcs.LGstat.MLarXiv:1904.00445v22019
Learn Beneficial Noise as Graph Augmentation
Siqi Huang, Yanchen Xu, Hongyuan Zhang +1
cs.LGstat.MLarXiv:2505.19024v12025
Federated Multi-Task Learning
Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi +1
cs.LGstat.MLarXiv:1705.10467v22017
Direct Feedback Alignment Provides Learning in Deep Neural Networks
Arild Nøkland
stat.MLcs.LGarXiv:1609.01596v52016
Decentralized Federated Learning: A Segmented Gossip Approach
Chenghao Hu, Jingyan Jiang, Zhi Wang
cs.LGcs.DCcs.NIarXiv:1908.07782v12019
Optimal Rates for Random Fourier Features
Bharath K. Sriperumbudur, Zoltan Szabo
math.STcs.LGmath.FAarXiv:1506.02155v22015
SparkNet: Training Deep Networks in Spark
Philipp Moritz, Robert Nishihara, Ion Stoica +1
stat.MLcs.DCcs.LGarXiv:1511.06051v42015
PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior
Sang-gil Lee, Heeseung Kim, Chaehun Shin +7
stat.MLcs.LGcs.SDarXiv:2106.06406v22021
Taylor Expansion of Discount Factors
Yunhao Tang, Mark Rowland, Rémi Munos +1
cs.LGstat.MLarXiv:2106.06170v22021
Continuous Learning in Single-Incremental-Task Scenarios
Davide Maltoni, Vincenzo Lomonaco
cs.LGcs.AIcs.CVarXiv:1806.08568v32018
Encoding-dependent generalization bounds for parametrized quantum circuits
Matthias C. Caro, Elies Gil-Fuster, Johannes Jakob Meyer +2
quant-phcs.ITmath.ITarXiv:2106.03880v32021
Weakly Supervised Disentanglement with Guarantees
Rui Shu, Yining Chen, Abhishek Kumar +2
cs.LGstat.MLarXiv:1910.09772v22019
Houdini: Fooling Deep Structured Prediction Models
Moustapha Cisse, Yossi Adi, Natalia Neverova +1
stat.MLcs.AIcs.CRarXiv:1707.05373v12017
Black-box $α$-divergence Minimization
José Miguel Hernández-Lobato, Yingzhen Li, Mark Rowland +3
stat.MLarXiv:1511.03243v32015
Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series
Dan Li, Dacheng Chen, Jonathan Goh +1
cs.LGstat.MLarXiv:1809.04758v32018
Hierarchical Variational Models
Rajesh Ranganath, Dustin Tran, David M. Blei
stat.MLcs.LGstat.COarXiv:1511.02386v22015
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities
Oliver T. Unke, Mihail Bogojeski, Michael Gastegger +3
physics.chem-phstat.MLarXiv:2106.02347v22021
Understanding the impact of entropy on policy optimization
Zafarali Ahmed, Nicolas Le Roux, Mohammad Norouzi +1
cs.LGstat.MLarXiv:1811.11214v52018
Leaner Transformers Can Easily Learn to Cluster
Charlotte Park, Kenneth L. Clarkson, Lior Horesh +2
cs.LGstat.MLarXiv:2610.09760v12026
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
Zonglin Li, Chong You, Srinadh Bhojanapalli +8
cs.LGcs.CLcs.CVarXiv:2210.06313v22022
Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network
Bai Jiang, Tung-yu Wu, Charles Zheng +1
stat.MEstat.COstat.MLarXiv:1510.02175v32015
IPO: Interior-point Policy Optimization under Constraints
Yongshuai Liu, Jiaxin Ding, Xin Liu
cs.LGmath.OCstat.MLarXiv:1910.09615v12019
Label Noise SGD Provably Prefers Flat Global Minimizers
Alex Damian, Tengyu Ma, Jason D. Lee
cs.LGcs.ITmath.OCarXiv:2106.06530v22021
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers
Yonatan Geifman, Guy Uziel, Ran El-Yaniv
cs.LGstat.MLarXiv:1805.08206v42018
Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning
Johnathon Shook, Tryambak Gangopadhyay, Linjiang Wu +3
cs.LGstat.MLarXiv:2006.13847v12020
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
Martin Mundt, Yongwon Hong, Iuliia Pliushch +1
cs.LGstat.MLarXiv:2009.01797v32020
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree
Chen-Yu Lee, Patrick W. Gallagher, Zhuowen Tu
stat.MLcs.LGcs.NEarXiv:1509.08985v22015
Identifying ODEs from Unstructured Data with Causal Representation Learning
Alessandro Trenta, Riccardo Massidda, Davide Bacciu +1
cs.LGcs.AIstat.MLarXiv:2609.37083v12026
DiBS: Differentiable Bayesian Structure Learning
Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf +1
cs.LGstat.MLarXiv:2105.11839v32021
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
Xiangyi Chen, Sijia Liu, Kaidi Xu +4
cs.LGmath.OCstat.MLarXiv:1910.06513v22019
Matched Queries for Curvature and Density at Branching Junctions
Ziqi Zhao, Qingjian Ni
stat.MLcs.LGarXiv:2609.01319v12026
Unbounded Characteristic and Universal Kernels
Jose Cribeiro-Ramallo, Florian Kalinke, Zoltán Szabó
math.STcs.LGstat.MLarXiv:2610.09731v12026
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
Marco Fraccaro, Simon Kamronn, Ulrich Paquet +1
stat.MLcs.LGarXiv:1710.05741v22017
Deep learning generalizes because the parameter-function map is biased towards simple functions
Guillermo Valle-Pérez, Chico Q. Camargo, Ard A. Louis
stat.MLcs.AIcs.LGarXiv:1805.08522v52018
Just Interpolate: Kernel "Ridgeless" Regression Can Generalize
Tengyuan Liang, Alexander Rakhlin
math.STcs.LGstat.MLarXiv:1808.00387v22018
Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
Bradly C. Stadie, Sergey Levine, Pieter Abbeel
cs.AIcs.LGstat.MLarXiv:1507.00814v32015
Functional linear regression from sparse to dense designs: a pooling-ridge method and minimax optimality
Shunxing Yan, Fang Yao
stat.MEcs.LGmath.STarXiv:2608.25468v12026
On Smoothing and Inference for Topic Models
Arthur Asuncion, Max Welling, Padhraic Smyth +1
cs.LGstat.MLarXiv:1205.2662v12012
RATT: Leveraging Unlabeled Data to Guarantee Generalization
Saurabh Garg, Sivaraman Balakrishnan, J. Zico Kolter +1
cs.LGstat.MLarXiv:2105.00303v22021
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction
Liang-Chieh Chen, Maxwell D. Collins, Yukun Zhu +5
cs.CVcs.LGstat.MLarXiv:1809.04184v12018
Character-Aware Neural Language Models
Yoon Kim, Yacine Jernite, David Sontag +1
cs.CLcs.NEstat.MLarXiv:1508.06615v42015
Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret
Jean Tarbouriech, Runlong Zhou, Simon S. Du +3
cs.LGstat.MLarXiv:2104.11186v22021
Learning Dexterous In-Hand Manipulation
OpenAI, Marcin Andrychowicz, Bowen Baker +14
cs.LGcs.AIcs.ROarXiv:1808.00177v52018
Learning PDE Time-Stepping with Neural Cellular Automata
Esha Saha, Hao Wang
cs.LGstat.MLarXiv:2608.30328v12026
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
Jiong Zhu, Yujun Yan, Lingxiao Zhao +3
cs.LGstat.MLarXiv:2006.11468v22020
A step towards procedural terrain generation with GANs
Christopher Beckham, Christopher Pal
stat.MLcs.CVarXiv:1707.03383v12017
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
Wieland Brendel, Jonas Rauber, Matthias Bethge
stat.MLcs.CRcs.CVarXiv:1712.04248v22017
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
Sanket Kamthe, Marc Peter Deisenroth
eess.SYstat.MLarXiv:1706.06491v22017
Dynamic Pricing in High-dimensions
Adel Javanmard, Hamid Nazerzadeh
stat.MLcs.LGarXiv:1609.07574v42016
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems
David R. Karger, Sewoong Oh, Devavrat Shah
cs.LGcs.DScs.HCarXiv:1110.3564v42011
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices
Caiwen Ding, Siyu Liao, Yanzhi Wang +13
cs.CVcs.AIcs.LGarXiv:1708.08917v12017
Artificial intelligence surrogates for treatment effect estimation with before-and-after data
Frances Dean, Anna Neufeld, Joshua Barrios +2
stat.MLcs.LGarXiv:2609.27180v12026
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
Alexander Immer, Matthias Bauer, Vincent Fortuin +2
stat.MLcs.LGarXiv:2104.04975v32021

Machine Learning (stat)

Continual Learning in Generative Adversarial Nets

Sparsifying Stochasticity, Not Capacity: Partial Stochasticity via Deep Weight Factorization of Prior Scales

Nonlinear Interference Mitigation via Deep Neural Networks

Deep reinforcement learning from human preferences

Robust Kernel Density Estimation

Flow Matching on General Geometries

Model-Based Reinforcement Learning via Meta-Policy Optimization

The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

Learn Beneficial Noise as Graph Augmentation

Federated Multi-Task Learning

Direct Feedback Alignment Provides Learning in Deep Neural Networks

Decentralized Federated Learning: A Segmented Gossip Approach

Optimal Rates for Random Fourier Features

SparkNet: Training Deep Networks in Spark

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior

Taylor Expansion of Discount Factors

Continuous Learning in Single-Incremental-Task Scenarios

Encoding-dependent generalization bounds for parametrized quantum circuits

Weakly Supervised Disentanglement with Guarantees

Houdini: Fooling Deep Structured Prediction Models

Black-box $α$-divergence Minimization

Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series

Hierarchical Variational Models

SE(3)-equivariant prediction of molecular wavefunctions and electronic densities

Understanding the impact of entropy on policy optimization

Leaner Transformers Can Easily Learn to Cluster

The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers

Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network

IPO: Interior-point Policy Optimization under Constraints

Label Noise SGD Provably Prefers Flat Global Minimizers

Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers

Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning

A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning

Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree

Identifying ODEs from Unstructured Data with Causal Representation Learning

DiBS: Differentiable Bayesian Structure Learning

ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization

Matched Queries for Curvature and Density at Branching Junctions

Unbounded Characteristic and Universal Kernels

A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning

Deep learning generalizes because the parameter-function map is biased towards simple functions

Just Interpolate: Kernel "Ridgeless" Regression Can Generalize

Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models

Functional linear regression from sparse to dense designs: a pooling-ridge method and minimax optimality

On Smoothing and Inference for Topic Models

RATT: Leveraging Unlabeled Data to Guarantee Generalization

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

Character-Aware Neural Language Models

Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret

Learning Dexterous In-Hand Manipulation

Learning PDE Time-Stepping with Neural Cellular Automata

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

A step towards procedural terrain generation with GANs

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control

Dynamic Pricing in High-dimensions

Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems

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

Artificial intelligence surrogates for treatment effect estimation with before-and-after data

Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning