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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61 to 120 of 6,778

Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT
Antti Koskela, Joonas Jälkö, Lukas Prediger +1
stat.MLcs.CRcs.LGarXiv:2006.07134v32020
Addressing Some Limitations of Transformers with Feedback Memory
Angela Fan, Thibaut Lavril, Edouard Grave +2
cs.LGcs.CLstat.MLarXiv:2002.09402v32020
Fair Adversarial Gradient Tree Boosting
Vincent Grari, Boris Ruf, Sylvain Lamprier +1
cs.LGcs.AIcs.CYarXiv:1911.05369v22019
Estimating individual treatment effect: generalization bounds and algorithms
Uri Shalit, Fredrik D. Johansson, David Sontag
stat.MLcs.AIcs.LGarXiv:1606.03976v52016
Addressing the Item Cold-start Problem by Attribute-driven Active Learning
Yu Zhu, Jinhao Lin, Shibi He +4
cs.IRcs.LGstat.MLarXiv:1805.09023v12018
Sparse MoEs meet Efficient Ensembles
James Urquhart Allingham, Florian Wenzel, Zelda E Mariet +10
cs.LGcs.CVstat.MLarXiv:2110.03360v22021
Beyond neural scaling laws: beating power law scaling via data pruning
Ben Sorscher, Robert Geirhos, Shashank Shekhar +2
cs.LGcs.AIcs.CVarXiv:2206.14486v62022
SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics
Kadierdan Kaheman, J. Nathan Kutz, Steven L. Brunton
cs.LGphysics.comp-phstat.MLarXiv:2004.02322v22020
Meta Label Correction for Noisy Label Learning
Guoqing Zheng, Ahmed Hassan Awadallah, Susan Dumais
cs.LGstat.MLarXiv:1911.03809v22019
Federated Optimization in Heterogeneous Networks
Tian Li, Anit Kumar Sahu, Manzil Zaheer +3
cs.LGstat.MLarXiv:1812.06127v52018
World Models
David Ha, Jürgen Schmidhuber
cs.LGstat.MLarXiv:1803.10122v42018
Probabilistic Fair Clustering
Seyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas +1
cs.LGcs.AIcs.DSarXiv:2006.10916v32020
Predictive Entropy Search for Multi-objective Bayesian Optimization
Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Amar Shah +1
stat.MLarXiv:1511.05467v32015
Finite Versus Infinite Neural Networks: an Empirical Study
Jaehoon Lee, Samuel S. Schoenholz, Jeffrey Pennington +4
cs.LGstat.MLarXiv:2007.15801v22020
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
Blake Woodworth, Jialei Wang, Adam Smith +2
math.OCcs.LGstat.MLarXiv:1805.10222v32018
Nonparametric semi-supervised learning of class proportions
Shantanu Jain, Martha White, Michael W. Trosset +1
stat.MLcs.LGarXiv:1601.01944v12016
Graph Kernels: A Survey
Giannis Nikolentzos, Giannis Siglidis, Michalis Vazirgiannis
stat.MLcs.LGarXiv:1904.12218v22019
Preservation of Log-Concavity and Convergence of Wasserstein-Fisher-Rao Gradient Flows
Francesca Romana Crucinio, Sahani Pathiraja
stat.MLcs.LGmath.PRarXiv:2609.18118v12026
Pay Only for Disagreement: Certified No-Regression Verdicts for Model Updates with Matching Label-Complexity Bounds
Vishnu Bindu Balachandran
cs.LGcs.AIcs.CVarXiv:2609.17560v12026
Variational Encoding of Complex Dynamics
Carlos X. Hernández, Hannah K. Wayment-Steele, Mohammad M. Sultan +2
stat.MLphysics.bio-phphysics.chem-pharXiv:1711.08576v22017
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
Pim de Haan, Maurice Weiler, Taco Cohen +1
cs.LGcs.CVstat.MLarXiv:2003.05425v32020
Dimension-Corrected Hitting Times for Heavy-Tailed Spectral Emergence in Neural Optimizer Dynamics
Zongmin Liu
cs.LGcs.NEstat.MLarXiv:2609.12994v12026
A Full Adam Theorem for Spectral Heavy-Tail Onset
Zongmin Liu
cs.LGmath.PRstat.MLarXiv:2609.12996v12026
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
Bastian Rieck, Matteo Togninalli, Christian Bock +4
cs.LGmath.ATstat.MLarXiv:1812.09764v32018
Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection
David Zimmerer, Simon A. A. Kohl, Jens Petersen +2
cs.LGstat.MLarXiv:1812.05941v12018
FT-ClipAct: Resilience Analysis of Deep Neural Networks and Improving their Fault Tolerance using Clipped Activation
Le-Ha Hoang, Muhammad Abdullah Hanif, Muhammad Shafique
cs.LGstat.MLarXiv:1912.00941v12019
Narrowing the Gap: Random Forests In Theory and In Practice
Misha Denil, David Matheson, Nando de Freitas
stat.MLcs.LGarXiv:1310.1415v12013
Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging
Antoine Guillot, Fabien Sauvet, Emmanuel H During +1
q-bio.QMcs.LGeess.SParXiv:1911.03221v42019
Covariate Selection for Doubly Robust Double/debiased Machine Learning Estimators for Causal Inference
Muwon Kwon, Peter M. Steiner
stat.MEstat.MLarXiv:2609.17238v12026
Probabilistic Recurrent State-Space Models
Andreas Doerr, Christian Daniel, Martin Schiegg +4
stat.MLarXiv:1801.10395v22018
On the disintegration of the stochastic majority vote: From PAC-Bayesian bounds to a self-bounding algorithm
Julien Bastian, Benjamin Leblanc, Pascal Germain +4
stat.MLcs.LGarXiv:2609.16803v12026
Sampling using $SU(N)$ gauge equivariant flows
Denis Boyda, Gurtej Kanwar, Sébastien Racanière +5
hep-latcs.LGstat.MLarXiv:2008.05456v22020
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors
Gilad Cohen, Guillermo Sapiro, Raja Giryes
cs.LGstat.MLarXiv:1909.06872v22019
A Comparative Analysis of Forecasting Financial Time Series Using ARIMA, LSTM, and BiLSTM
Sima Siami-Namini, Neda Tavakoli, Akbar Siami Namin
cs.LGcs.CEcs.PFarXiv:1911.09512v12019
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks
Hang Gao, Zheng Shou, Alireza Zareian +2
cs.LGstat.MLarXiv:1810.11730v32018
Towards better understanding of gradient-based attribution methods for Deep Neural Networks
Marco Ancona, Enea Ceolini, Cengiz Öztireli +1
cs.LGstat.MLarXiv:1711.06104v42017
Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring
Albert Vilamala, Kristoffer H. Madsen, Lars K. Hansen
cs.CVstat.MLarXiv:1710.00633v12017
Diversity-Driven Exploration Strategy for Deep Reinforcement Learning
Zhang-Wei Hong, Tzu-Yun Shann, Shih-Yang Su +2
cs.AIstat.MLarXiv:1802.04564v22018
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning
Silviu Pitis, Harris Chan, Stephen Zhao +2
cs.LGcs.AIcs.ROarXiv:2007.02832v12020
Speed Limit for Information Acquisition in Stochastic Learning Dynamics
Shuta Kobayashi, Andreas Dechant
cond-mat.stat-mechcs.LGstat.MLarXiv:2609.08219v12026
A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks
César A. Uribe, Soomin Lee, Alexander Gasnikov +1
math.OCcs.DCcs.MAarXiv:1809.00710v32018
Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity
Joana Lorenz, Maria Inês Silva, David Aparício +2
cs.LGstat.MLarXiv:2005.14635v22020
Transfer Learning for Named-Entity Recognition with Neural Networks
Ji Young Lee, Franck Dernoncourt, Peter Szolovits
cs.CLcs.AIcs.NEarXiv:1705.06273v12017
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
cs.LGcs.AIstat.MLarXiv:2006.07500v32020
Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective
Muhammad Abdullah Jamal, Matthew Brown, Ming-Hsuan Yang +2
cs.CVcs.LGstat.MLarXiv:2003.10780v12020
Combating noisy labels by agreement: A joint training method with co-regularization
Hongxin Wei, Lei Feng, Xiangyu Chen +1
cs.CVcs.LGstat.MLarXiv:2003.02752v32020
Knowledge Graph Embedding for Link Prediction: A Comparative Analysis
Andrea Rossi, Donatella Firmani, Antonio Matinata +2
cs.LGcs.DBstat.MLarXiv:2002.00819v42020
Variational Graph Recurrent Neural Networks
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield +3
cs.LGstat.MLarXiv:1908.09710v32019
Uncertainty-based Continual Learning with Adaptive Regularization
Hongjoon Ahn, Sungmin Cha, Donggyu Lee +1
cs.LGstat.MLarXiv:1905.11614v32019
Simplifying Graph Convolutional Networks
Felix Wu, Tianyi Zhang, Amauri Holanda de Souza +3
cs.LGstat.MLarXiv:1902.07153v22019
Formal Limitations on the Measurement of Mutual Information
David McAllester, Karl Stratos
cs.ITcs.LGstat.MLarXiv:1811.04251v42018
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
Stefan Falkner, Aaron Klein, Frank Hutter
cs.LGstat.MLarXiv:1807.01774v12018
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks
Chunyuan Li, Changyou Chen, David Carlson +1
stat.MLarXiv:1512.07666v12015
Active Authentication on Mobile Devices via Stylometry, Application Usage, Web Browsing, and GPS Location
Lex Fridman, Steven Weber, Rachel Greenstadt +1
cs.CRstat.MLarXiv:1503.08479v12015
Multi-Agent Actor-Critic with Hierarchical Graph Attention Network
Heechang Ryu, Hayong Shin, Jinkyoo Park
cs.LGcs.AIcs.MAarXiv:1909.12557v22019
Improving GANs Using Optimal Transport
Tim Salimans, Han Zhang, Alec Radford +1
cs.LGstat.MLarXiv:1803.05573v12018
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider +2
cs.LGstat.MLarXiv:1802.07191v32018
Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement
Jason Lee, Elman Mansimov, Kyunghyun Cho
cs.LGcs.CLstat.MLarXiv:1802.06901v32018
Tree-CNN: A Hierarchical Deep Convolutional Neural Network for Incremental Learning
Deboleena Roy, Priyadarshini Panda, Kaushik Roy
cs.CVcs.AIeess.IVarXiv:1802.05800v32018
Efficient Exploration through Bayesian Deep Q-Networks
Kamyar Azizzadenesheli, Animashree Anandkumar
cs.AIcs.LGstat.MLarXiv:1802.04412v42018

Machine Learning (stat)

Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT

Addressing Some Limitations of Transformers with Feedback Memory

Fair Adversarial Gradient Tree Boosting

Estimating individual treatment effect: generalization bounds and algorithms

Addressing the Item Cold-start Problem by Attribute-driven Active Learning

Sparse MoEs meet Efficient Ensembles

Beyond neural scaling laws: beating power law scaling via data pruning

SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics

Meta Label Correction for Noisy Label Learning

Federated Optimization in Heterogeneous Networks

World Models

Probabilistic Fair Clustering

Predictive Entropy Search for Multi-objective Bayesian Optimization

Finite Versus Infinite Neural Networks: an Empirical Study

Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization

Nonparametric semi-supervised learning of class proportions

Graph Kernels: A Survey

Preservation of Log-Concavity and Convergence of Wasserstein-Fisher-Rao Gradient Flows

Pay Only for Disagreement: Certified No-Regression Verdicts for Model Updates with Matching Label-Complexity Bounds

Variational Encoding of Complex Dynamics

Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs

Dimension-Corrected Hitting Times for Heavy-Tailed Spectral Emergence in Neural Optimizer Dynamics

A Full Adam Theorem for Spectral Heavy-Tail Onset

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology

Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection

FT-ClipAct: Resilience Analysis of Deep Neural Networks and Improving their Fault Tolerance using Clipped Activation

Narrowing the Gap: Random Forests In Theory and In Practice

Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging

Covariate Selection for Doubly Robust Double/debiased Machine Learning Estimators for Causal Inference

Probabilistic Recurrent State-Space Models

On the disintegration of the stochastic majority vote: From PAC-Bayesian bounds to a self-bounding algorithm

Sampling using $SU(N)$ gauge equivariant flows

Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors

A Comparative Analysis of Forecasting Financial Time Series Using ARIMA, LSTM, and BiLSTM

Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks

Towards better understanding of gradient-based attribution methods for Deep Neural Networks

Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring

Diversity-Driven Exploration Strategy for Deep Reinforcement Learning

Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning

Speed Limit for Information Acquisition in Stochastic Learning Dynamics

A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks

Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity

Transfer Learning for Named-Entity Recognition with Neural Networks

Domain Generalization using Causal Matching

Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective

Combating noisy labels by agreement: A joint training method with co-regularization

Knowledge Graph Embedding for Link Prediction: A Comparative Analysis

Variational Graph Recurrent Neural Networks

Uncertainty-based Continual Learning with Adaptive Regularization

Simplifying Graph Convolutional Networks

Formal Limitations on the Measurement of Mutual Information

BOHB: Robust and Efficient Hyperparameter Optimization at Scale

Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks

Active Authentication on Mobile Devices via Stylometry, Application Usage, Web Browsing, and GPS Location

Multi-Agent Actor-Critic with Hierarchical Graph Attention Network

Improving GANs Using Optimal Transport

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement

Tree-CNN: A Hierarchical Deep Convolutional Neural Network for Incremental Learning

Efficient Exploration through Bayesian Deep Q-Networks