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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8,761 to 8,820 of 9,665

Rethinking the Hyperparameters for Fine-tuning
Hao Li, Pratik Chaudhari, Hao Yang +4
cs.CVcs.LGstat.MLarXiv:2002.11770v12020
Deep Learning in Alzheimer's disease: Diagnostic Classification and Prognostic Prediction using Neuroimaging Data
Taeho Jo, Kwangsik Nho, Andrew J. Saykin
eess.IVcs.LGstat.MLarXiv:1905.00931v42019
FetchSGD: Communication-Efficient Federated Learning with Sketching
Daniel Rothchild, Ashwinee Panda, Enayat Ullah +5
cs.LGstat.MLarXiv:2007.07682v22020
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization
Ohad Shamir
cs.LGmath.OCstat.MLarXiv:1209.2388v32012
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
Yuxin Chen, Emmanuel J. Candes
cs.ITcs.LGmath.NAarXiv:1505.05114v22015
Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search
Arber Zela, Aaron Klein, Stefan Falkner +1
cs.LGcs.AIcs.CVarXiv:1807.06906v12018
Interpretable Distribution Features with Maximum Testing Power
Wittawat Jitkrittum, Zoltan Szabo, Kacper Chwialkowski +1
stat.MLcs.LGarXiv:1605.06796v22016
Minimax Rates of Estimation for Sparse PCA in High Dimensions
Vincent Q. Vu, Jing Lei
stat.MLcs.LGmath.STarXiv:1202.0786v22012
Deep Transfer Learning for Cross-domain Activity Recognition
Jindong Wang, Vincent W. Zheng, Yiqiang Chen +1
eess.IVstat.MLarXiv:1807.07963v22018
MMA Training: Direct Input Space Margin Maximization through Adversarial Training
Gavin Weiguang Ding, Yash Sharma, Kry Yik Chau Lui +1
cs.LGcs.NEstat.MLarXiv:1812.02637v42018
Sparse Signal Estimation by Maximally Sparse Convex Optimization
Ivan W. Selesnick, Ilker Bayram
cs.LGstat.MLarXiv:1302.5729v32013
Federated Accelerated Stochastic Gradient Descent
Honglin Yuan, Tengyu Ma
cs.LGcs.DCmath.OCarXiv:2006.08950v42020
Unconstrained Monotonic Neural Networks
Antoine Wehenkel, Gilles Louppe
cs.LGcs.NEstat.MLarXiv:1908.05164v32019
On Analog Gradient Descent Learning over Multiple Access Fading Channels
Tomer Sery, Kobi Cohen
cs.LGcs.ITstat.MLarXiv:1908.07463v12019
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks
Yuening Li, Xiao Huang, Jundong Li +2
cs.LGstat.MLarXiv:1908.03849v32019
Distributed Matrix Completion and Robust Factorization
Lester Mackey, Ameet Talwalkar, Michael I. Jordan
cs.LGcs.DSmath.NAarXiv:1107.0789v72011
Non-stationary Stochastic Optimization
O. Besbes, Y. Gur, A. Zeevi
math.PRcs.LGstat.MLarXiv:1307.5449v22013
Learning Texture Manifolds with the Periodic Spatial GAN
Urs Bergmann, Nikolay Jetchev, Roland Vollgraf
cs.CVstat.MLarXiv:1705.06566v22017
Controlling Neural Level Sets
Matan Atzmon, Niv Haim, Lior Yariv +3
cs.LGstat.MLarXiv:1905.11911v22019
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III
Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan +3
cs.LGstat.MLarXiv:1907.08322v22019
The power of deeper networks for expressing natural functions
David Rolnick, Max Tegmark
cs.LGcs.NEstat.MLarXiv:1705.05502v22017
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
Yudong Chen, Lili Su, Jiaming Xu
cs.DCcs.CRcs.LGarXiv:1705.05491v22017
Graph Unlearning
Min Chen, Zhikun Zhang, Tianhao Wang +3
cs.LGcs.AIcs.CRarXiv:2103.14991v22021
MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims
Isabelle Augenstein, Christina Lioma, Dongsheng Wang +4
cs.CLcs.IRcs.LGarXiv:1909.03242v22019
Statistical Feature Augmentation for Anomaly Detection in Dynamic Graphs
Philipp Schlinge, Jean-Luc Schnipper, Martin Atzmueller
cs.SIcs.LGstat.MLarXiv:2609.02965v12026
Iterative Random Forests to detect predictive and stable high-order interactions
Sumanta Basu, Karl Kumbier, James B. Brown +1
stat.MLq-bio.GNarXiv:1706.08457v42017
Learning interpretable continuous-time models of latent stochastic dynamical systems
Lea Duncker, Gergo Bohner, Julien Boussard +1
stat.MLcs.LGmath.DSarXiv:1902.04420v12019
Robust Reinforcement Learning using Offline Data
Kishan Panaganti, Zaiyan Xu, Dileep Kalathil +1
cs.LGcs.AIstat.MLarXiv:2208.05129v22022
AdaGAN: Boosting Generative Models
Ilya Tolstikhin, Sylvain Gelly, Olivier Bousquet +2
stat.MLcs.LGarXiv:1701.02386v22017
Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm
Simon Fischer, Ingo Steinwart
stat.MLarXiv:1702.07254v32017
Eigenvalues of the Hessian in Deep Learning: The Origin of Symmetry and Its Breaking
Yossi Arjevani
cs.LGmath.OCstat.MLarXiv:2610.09919v12026
Reconciling Universal and Uniform Learning with $Q$-Aggregation
Mikael Møller Høgsgaard, Patrick Rebeschini, Tobias Wegel
math.STstat.MLarXiv:2609.05041v12026
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games
Kaiqing Zhang, Zhuoran Yang, Tamer Başar
cs.LGcs.GTcs.SYarXiv:1906.00729v42019
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki +3
stat.MLcs.LGmath.STarXiv:2205.01445v12022
Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach
Pierre Courtiol, Eric W. Tramel, Marc Sanselme +1
cs.CVcs.LGstat.MLarXiv:1802.02212v22018
Secure Federated Transfer Learning
Yang Liu, Yan Kang, Chaoping Xing +2
cs.LGstat.MLarXiv:1812.03337v22018
Task Agnostic Continual Learning Using Online Variational Bayes
Chen Zeno, Itay Golan, Elad Hoffer +1
stat.MLcs.LGarXiv:1803.10123v32018
LESS is More: Rethinking Probabilistic Models of Human Behavior
Andreea Bobu, Dexter R. R. Scobee, Jaime F. Fisac +2
cs.ROcs.AIcs.HCarXiv:2001.04465v12020
Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
Mathias Kraus, Stefan Feuerriegel
cs.LGstat.MLarXiv:1907.05146v22019
Towards Adversarial Retinal Image Synthesis
Pedro Costa, Adrian Galdran, Maria Inês Meyer +4
cs.CVcs.LGstat.MLarXiv:1701.08974v12017
GRATIS: GeneRAting TIme Series with diverse and controllable characteristics
Yanfei Kang, Rob J Hyndman, Feng Li
stat.MLcs.LGstat.COarXiv:1903.02787v22019
WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling
Hao Zhang, Bo Chen, Dandan Guo +1
stat.MLstat.APstat.COarXiv:1803.01328v22018
Characterizing Diabetes, Diet, Exercise, and Obesity Comments on Twitter
Amir Karami, Alicia A. Dahl, Gabrielle Turner-McGrievy +2
cs.SIcs.CLstat.AParXiv:1709.07916v12017
Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction
Pedram Daee, Tomi Peltola, Marta Soare +1
cs.AIcs.HCcs.LGarXiv:1612.03328v22016
Human-in-the-Loop Interpretability Prior
Isaac Lage, Andrew Slavin Ross, Been Kim +2
stat.MLcs.LGarXiv:1805.11571v22018
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking
Patrick H. Chen, Si Si, Yang Li +2
cs.CLcs.AIcs.LGarXiv:1806.06950v12018
Online Embedding Compression for Text Classification using Low Rank Matrix Factorization
Anish Acharya, Rahul Goel, Angeliki Metallinou +1
cs.LGcs.CLcs.NAarXiv:1811.00641v12018
Fully-hierarchical fine-grained prosody modeling for interpretable speech synthesis
Guangzhi Sun, Yu Zhang, Ron J. Weiss +3
eess.AScs.LGcs.SDarXiv:2002.03785v12020
Multimodal Machine Learning for Automated ICD Coding
Keyang Xu, Mike Lam, Jingzhi Pang +9
cs.LGstat.MLarXiv:1810.13348v42018
A Transformer-based Audio Captioning Model with Keyword Estimation
Yuma Koizumi, Ryo Masumura, Kyosuke Nishida +2
eess.AScs.LGcs.SDarXiv:2007.00222v22020
Sequential Scenario-Specific Meta Learner for Online Recommendation
Zhengxiao Du, Xiaowei Wang, Hongxia Yang +2
cs.IRcs.LGstat.MLarXiv:1906.00391v12019
When is a Convolutional Filter Easy To Learn?
Simon S. Du, Jason D. Lee, Yuandong Tian
cs.LGcs.AIcs.CVarXiv:1709.06129v22017
People on Drugs: Credibility of User Statements in Health Communities
Subhabrata Mukherjee, Gerhard Weikum, Cristian Danescu-Niculescu-Mizil
cs.AIcs.CLcs.IRarXiv:1705.02522v12017
Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data
Rui Dai, Shenkun Xu, Qian Gu +2
cs.LGstat.MLarXiv:2006.12715v12020
Profit Driven Decision Trees for Churn Prediction
Sebastiaan Höppner, Eugen Stripling, Bart Baesens +2
stat.MLcs.LGstat.AParXiv:1712.08101v12017
A XGBoost risk model via feature selection and Bayesian hyper-parameter optimization
Yan Wang, Xuelei Sherry Ni
stat.MLcs.LGarXiv:1901.08433v12019
Visual Sentiment Prediction with Deep Convolutional Neural Networks
Can Xu, Suleyman Cetintas, Kuang-Chih Lee +1
cs.CVcs.NEstat.MLarXiv:1411.5731v12014
A Multimodal Explainable Deep Learning Framework for Alzheimer's Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data
Yusuf Brima, Marcellin Atemkeng, Lakshmana Rao Namamula +1
cs.CVstat.MLarXiv:2609.12410v12026
Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning
Qingkai Liang, Fanyu Que, Eytan Modiano
cs.AIcs.LGstat.MLarXiv:1802.06480v12018
On the Difference Between the Information Bottleneck and the Deep Information Bottleneck
Aleksander Wieczorek, Volker Roth
cs.LGcs.ITmath.ITarXiv:1912.13480v12019

Machine Learning (stat)

Rethinking the Hyperparameters for Fine-tuning

Deep Learning in Alzheimer's disease: Diagnostic Classification and Prognostic Prediction using Neuroimaging Data

FetchSGD: Communication-Efficient Federated Learning with Sketching

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

Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems

Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search

Interpretable Distribution Features with Maximum Testing Power

Minimax Rates of Estimation for Sparse PCA in High Dimensions

Deep Transfer Learning for Cross-domain Activity Recognition

MMA Training: Direct Input Space Margin Maximization through Adversarial Training

Sparse Signal Estimation by Maximally Sparse Convex Optimization

Federated Accelerated Stochastic Gradient Descent

Unconstrained Monotonic Neural Networks

On Analog Gradient Descent Learning over Multiple Access Fading Channels

SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks

Distributed Matrix Completion and Robust Factorization

Non-stationary Stochastic Optimization

Learning Texture Manifolds with the Periodic Spatial GAN

Controlling Neural Level Sets

MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III

The power of deeper networks for expressing natural functions

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent

Graph Unlearning

MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims

Statistical Feature Augmentation for Anomaly Detection in Dynamic Graphs

Iterative Random Forests to detect predictive and stable high-order interactions

Learning interpretable continuous-time models of latent stochastic dynamical systems

Robust Reinforcement Learning using Offline Data

AdaGAN: Boosting Generative Models

Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm

Eigenvalues of the Hessian in Deep Learning: The Origin of Symmetry and Its Breaking

Reconciling Universal and Uniform Learning with $Q$-Aggregation

Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games

High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation

Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach

Secure Federated Transfer Learning

Task Agnostic Continual Learning Using Online Variational Bayes

LESS is More: Rethinking Probabilistic Models of Human Behavior

Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences

Towards Adversarial Retinal Image Synthesis

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics

WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling

Characterizing Diabetes, Diet, Exercise, and Obesity Comments on Twitter

Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction

Human-in-the-Loop Interpretability Prior

GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking

Online Embedding Compression for Text Classification using Low Rank Matrix Factorization

Fully-hierarchical fine-grained prosody modeling for interpretable speech synthesis

Multimodal Machine Learning for Automated ICD Coding

A Transformer-based Audio Captioning Model with Keyword Estimation

Sequential Scenario-Specific Meta Learner for Online Recommendation

When is a Convolutional Filter Easy To Learn?

People on Drugs: Credibility of User Statements in Health Communities

Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data

Profit Driven Decision Trees for Churn Prediction

A XGBoost risk model via feature selection and Bayesian hyper-parameter optimization

Visual Sentiment Prediction with Deep Convolutional Neural Networks

A Multimodal Explainable Deep Learning Framework for Alzheimer's Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data

Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

On the Difference Between the Information Bottleneck and the Deep Information Bottleneck