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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2,701 to 2,760 of 6,780

A computational approach to maximum likelihood thresholds for colored Gaussian graphical models
Roser Homs, Olga Kuznetsova, Bernadette J. Stolz
stat.MLcs.LGmath.AGarXiv:2609.02382v12026
Topological Autoencoders
Michael Moor, Max Horn, Bastian Rieck +1
cs.LGmath.ATstat.MLarXiv:1906.00722v52019
Prediction and optimization of mechanical properties of composites using convolutional neural networks
Diab W. Abueidda, Mohammad Almasri, Rami Ammourah +3
cs.LGphysics.comp-phstat.MLarXiv:1906.00094v12019
Ternary Compression for Communication-Efficient Federated Learning
Jinjin Xu, Wenli Du, Ran Cheng +2
cs.LGcs.DCstat.MLarXiv:2003.03564v22020
Predicting Race and Ethnicity From the Sequence of Characters in a Name
Rajashekar Chintalapati, Suriyan Laohaprapanon, Gaurav Sood
stat.APstat.MLarXiv:1805.02109v22018
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
Ángel Alexander Cabrera, Will Epperson, Fred Hohman +3
cs.LGstat.MLarXiv:1904.05419v42019
Predicting Student Dropout in Higher Education
Lovenoor Aulck, Nishant Velagapudi, Joshua Blumenstock +1
stat.MLcs.CYarXiv:1606.06364v42016
Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data
Yanru Qu, Bohui Fang, Weinan Zhang +5
cs.IRcs.LGstat.MLarXiv:1807.00311v12018
Laplacian Regularized Few-Shot Learning
Imtiaz Masud Ziko, Jose Dolz, Eric Granger +1
cs.LGcs.CVstat.MLarXiv:2006.15486v32020
True to the Model or True to the Data?
Hugh Chen, Joseph D. Janizek, Scott Lundberg +1
cs.LGstat.MLarXiv:2006.16234v12020
Universal Inference
Larry Wasserman, Aaditya Ramdas, Sivaraman Balakrishnan
math.STstat.MEstat.MLarXiv:1912.11436v42019
New Algorithms for Learning Incoherent and Overcomplete Dictionaries
Sanjeev Arora, Rong Ge, Ankur Moitra
cs.DScs.LGstat.MLarXiv:1308.6273v52013
Copula Transformations for Data-Consistent Inversion
Troy Butler, Tianyi Jiang, João Silva +2
stat.MLmath.OCmath.PRarXiv:2609.02832v12026
Behaviour Suite for Reinforcement Learning
Ian Osband, Yotam Doron, Matteo Hessel +11
cs.LGcs.AIstat.MLarXiv:1908.03568v32019
Test-Time Adaptable Neural Networks for Robust Medical Image Segmentation
Neerav Karani, Ertunc Erdil, Krishna Chaitanya +1
eess.IVcs.CVcs.LGarXiv:2004.04668v42020
Penalized Likelihood Methods for Estimation of Sparse High Dimensional Directed Acyclic Graphs
Ali Shojaie, George Michailidis
stat.MLmath.STstat.MEarXiv:0911.5439v12009
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization
Ohad Shamir
cs.LGmath.OCstat.MLarXiv:1209.2388v32012
Optimal Sparse Decision Trees
Xiyang Hu, Cynthia Rudin, Margo Seltzer
cs.LGstat.MLarXiv:1904.12847v62019
Distributed optimization of deeply nested systems
Miguel Á. Carreira-Perpiñán, Weiran Wang
cs.LGcs.NEmath.OCarXiv:1212.5921v12012
Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis
Soham Gadgil, Qingyu Zhao, Adolf Pfefferbaum +3
cs.LGstat.MLarXiv:2003.10613v32020
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
Derek Lim, Joshua Robinson, Lingxiao Zhao +4
cs.LGstat.MLarXiv:2202.13013v42022
Contextual Stochastic Block Models
Yash Deshpande, Andrea Montanari, Elchanan Mossel +1
cs.SIcs.LGstat.MLarXiv:1807.09596v12018
Smooth and Sparse Optimal Transport
Mathieu Blondel, Vivien Seguy, Antoine Rolet
stat.MLcs.LGarXiv:1710.06276v22017
Tightening Mutual Information Based Bounds on Generalization Error
Yuheng Bu, Shaofeng Zou, Venugopal V. Veeravalli
cs.LGstat.MLarXiv:1901.04609v22019
Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation
Sarah Tan, Rich Caruana, Giles Hooker +1
stat.MLcs.AIcs.LGarXiv:1710.06169v42017
Federated Accelerated Stochastic Gradient Descent
Honglin Yuan, Tengyu Ma
cs.LGcs.DCmath.OCarXiv:2006.08950v42020
Full-Model Optimality for Tunable Linear Generative Priors in Compressed Sensing
Zhaoming Li, Paul Hand
stat.MLcs.LGarXiv:2609.02790v12026
Relational Autoencoder for Feature Extraction
Qinxue Meng, Daniel Catchpoole, David Skillicorn +1
cs.LGstat.MLarXiv:1802.03145v12018
A Model for Learned Bloom Filters, and Optimizing by Sandwiching
Michael Mitzenmacher
cs.LGcs.DBstat.MLarXiv:1901.00902v12019
Estimation of Simultaneously Sparse and Low Rank Matrices
Emile Richard, Pierre-Andre Savalle, Nicolas Vayatis
cs.DScs.LGmath.NAarXiv:1206.6474v12012
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents
Alex Mott, Daniel Zoran, Mike Chrzanowski +2
cs.LGstat.MLarXiv:1906.02500v12019
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability
Kai Y. Xiao, Vincent Tjeng, Nur Muhammad Shafiullah +1
cs.LGcs.CRcs.NEarXiv:1809.03008v32018
Learning Predictive Representations for Deformable Objects Using Contrastive Estimation
Wilson Yan, Ashwin Vangipuram, Pieter Abbeel +1
cs.LGcs.CVcs.ROarXiv:2003.05436v12020
Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
Carles Domingo-Enrich, Michal Drozdzal, Brian Karrer +1
cs.LGmath.OCstat.MLarXiv:2409.08861v52024
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
Jaehong Yoon, Saehoon Kim, Eunho Yang +1
cs.LGstat.MLarXiv:1902.09432v32019
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation
Mingyuan Zhou, Huangjie Zheng, Zhendong Wang +2
cs.LGcs.AIcs.CVarXiv:2404.04057v32024
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
Amir-Hossein Karimi, Julius von Kügelgen, Bernhard Schölkopf +1
cs.LGcs.AIstat.MLarXiv:2006.06831v32020
Centripetal SGD for Pruning Very Deep Convolutional Networks with Complicated Structure
Xiaohan Ding, Guiguang Ding, Yuchen Guo +1
cs.LGcs.CVstat.MLarXiv:1904.03837v12019
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
Alicia Curth, Mihaela van der Schaar
stat.MLcs.LGarXiv:2101.10943v22021
Learning to Branch for Multi-Task Learning
Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht
cs.LGcs.CVstat.MLarXiv:2006.01895v22020
When to use parametric models in reinforcement learning?
Hado van Hasselt, Matteo Hessel, John Aslanides
cs.LGcs.AIstat.MLarXiv:1906.05243v12019
Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret
Raman Arora, Ofer Dekel, Ambuj Tewari
cs.LGstat.MLarXiv:1206.6400v12012
From topology learning to graph generation: A unifying perspective
Xiaowen Dong, Hoi-To Wai, Siheng Chen +2
stat.MLcs.LGeess.SParXiv:2609.02286v12026
Molecular geometry prediction using a deep generative graph neural network
Elman Mansimov, Omar Mahmood, Seokho Kang +1
cs.LGphysics.comp-phstat.MLarXiv:1904.00314v22019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Jonathan Shen, Patrick Nguyen, Yonghui Wu +88
cs.LGstat.MLarXiv:1902.08295v12019
Battery health prediction under generalized conditions using a Gaussian process transition model
Robert R. Richardson, Michael A. Osborne, David A. Howey
stat.APstat.MLarXiv:1807.06350v12018
Cycle Consistent Adversarial Denoising Network for Multiphase Coronary CT Angiography
Eunhee Kang, Hyun Jung Koo, Dong Hyun Yang +2
cs.CVcs.AIcs.LGarXiv:1806.09748v32018
Using Natural Language for Reward Shaping in Reinforcement Learning
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
cs.LGcs.AIstat.MLarXiv:1903.02020v22019
CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling
Ning Miao, Hao Zhou, Lili Mou +2
cs.CLcs.AIcs.LGarXiv:1811.10996v12018
Deep Reinforcement Learning for Imbalanced Classification
Enlu Lin, Qiong Chen, Xiaoming Qi
cs.LGcs.AIstat.MLarXiv:1901.01379v12019
FedSplit: An algorithmic framework for fast federated optimization
Reese Pathak, Martin J. Wainwright
cs.LGmath.OCstat.MLarXiv:2005.05238v12020
Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL
Anusha Nagabandi, Chelsea Finn, Sergey Levine
cs.LGcs.AIcs.ROarXiv:1812.07671v22018
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
Ryan L. Murphy, Balasubramaniam Srinivasan, Vinayak Rao +1
cs.LGstat.MLarXiv:1811.01900v32018
Harmless interpolation of noisy data in regression
Vidya Muthukumar, Kailas Vodrahalli, Vignesh Subramanian +1
cs.LGstat.MLarXiv:1903.09139v22019
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits
Mikołaj Sacha, Mikołaj Błaż, Piotr Byrski +5
cs.LGphysics.chem-phstat.MLarXiv:2006.15426v22020
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes
Nathan Kallus, Masatoshi Uehara
cs.LGcs.AIstat.MLarXiv:1908.08526v32019
Capacity and Trainability in Recurrent Neural Networks
Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
stat.MLcs.AIcs.LGarXiv:1611.09913v32016
Generative and Discriminative Text Classification with Recurrent Neural Networks
Dani Yogatama, Chris Dyer, Wang Ling +1
stat.MLcs.CLcs.LGarXiv:1703.01898v22017
Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition
Dimitrios Kollias, Stefanos Zafeiriou
cs.CVcs.AIcs.LGarXiv:1811.07770v22018
A General Approach to Adding Differential Privacy to Iterative Training Procedures
H. Brendan McMahan, Galen Andrew, Ulfar Erlingsson +4
cs.LGstat.MLarXiv:1812.06210v22018

Machine Learning (stat)

A computational approach to maximum likelihood thresholds for colored Gaussian graphical models

Topological Autoencoders

Prediction and optimization of mechanical properties of composites using convolutional neural networks

Ternary Compression for Communication-Efficient Federated Learning

Predicting Race and Ethnicity From the Sequence of Characters in a Name

FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning

Predicting Student Dropout in Higher Education

Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data

Laplacian Regularized Few-Shot Learning

True to the Model or True to the Data?

Universal Inference

New Algorithms for Learning Incoherent and Overcomplete Dictionaries

Copula Transformations for Data-Consistent Inversion

Behaviour Suite for Reinforcement Learning

Test-Time Adaptable Neural Networks for Robust Medical Image Segmentation

Penalized Likelihood Methods for Estimation of Sparse High Dimensional Directed Acyclic Graphs

On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization

Optimal Sparse Decision Trees

Distributed optimization of deeply nested systems

Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis

Sign and Basis Invariant Networks for Spectral Graph Representation Learning

Contextual Stochastic Block Models

Smooth and Sparse Optimal Transport

Tightening Mutual Information Based Bounds on Generalization Error

Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation

Federated Accelerated Stochastic Gradient Descent

Full-Model Optimality for Tunable Linear Generative Priors in Compressed Sensing

Relational Autoencoder for Feature Extraction

A Model for Learned Bloom Filters, and Optimizing by Sandwiching

Estimation of Simultaneously Sparse and Low Rank Matrices

Towards Interpretable Reinforcement Learning Using Attention Augmented Agents

Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability

Learning Predictive Representations for Deformable Objects Using Contrastive Estimation

Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control

Scalable and Order-robust Continual Learning with Additive Parameter Decomposition

Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation

Algorithmic recourse under imperfect causal knowledge: a probabilistic approach

Centripetal SGD for Pruning Very Deep Convolutional Networks with Complicated Structure

Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms

Learning to Branch for Multi-Task Learning

When to use parametric models in reinforcement learning?

Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret

From topology learning to graph generation: A unifying perspective

Molecular geometry prediction using a deep generative graph neural network

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

Battery health prediction under generalized conditions using a Gaussian process transition model

Cycle Consistent Adversarial Denoising Network for Multiphase Coronary CT Angiography

Using Natural Language for Reward Shaping in Reinforcement Learning

CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling

Deep Reinforcement Learning for Imbalanced Classification

FedSplit: An algorithmic framework for fast federated optimization

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

Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs

Harmless interpolation of noisy data in regression

Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits

Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes

Capacity and Trainability in Recurrent Neural Networks

Generative and Discriminative Text Classification with Recurrent Neural Networks

Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition

A General Approach to Adding Differential Privacy to Iterative Training Procedures