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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241 to 300 of 6,781

Ensemble Methods as a Defense to Adversarial Perturbations Against Deep Neural Networks
Thilo Strauss, Markus Hanselmann, Andrej Junginger +1
stat.MLcs.LGarXiv:1709.03423v22017
IQP Born Machines under Data-dependent and Agnostic Initialization Strategies
Sacha Lerch, Joseph Bowles, Ricard Puig +3
quant-phcs.LGstat.MLarXiv:2603.14576v12026
Sharp Bounds on the Approximation Rates, Metric Entropy, and $n$-widths of Shallow Neural Networks
Jonathan W. Siegel, Jinchao Xu
stat.MLcs.ITcs.LGarXiv:2101.12365v102021
Particle Filter Networks with Application to Visual Localization
Peter Karkus, David Hsu, Wee Sun Lee
cs.ROcs.AIcs.CVarXiv:1805.08975v32018
DeepHeart: Semi-Supervised Sequence Learning for Cardiovascular Risk Prediction
Brandon Ballinger, Johnson Hsieh, Avesh Singh +8
cs.LGcs.AIstat.MLarXiv:1802.02511v12018
Dynamic Pricing in High-dimensions
Adel Javanmard, Hamid Nazerzadeh
stat.MLcs.LGarXiv:1609.07574v42016
Evaluating Reinforcement Learning Algorithms in Observational Health Settings
Omer Gottesman, Fredrik Johansson, Joshua Meier +17
cs.LGstat.MLarXiv:1805.12298v12018
KVCOMM: Online Cross-context KV-cache Communication for Efficient LLM-based Multi-agent Systems
Hancheng Ye, Zhengqi Gao, Mingyuan Ma +8
cs.MAcs.AIstat.MLarXiv:2510.12872v22025
MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer
Gino Brunner, Andres Konrad, Yuyi Wang +1
cs.SDcs.LGeess.ASarXiv:1809.07600v12018
Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting
Bowen Zhang, Hsiu-Wen Cheng, Hongyu Yang +9
stat.MLcs.LGarXiv:2609.11872v12026
Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact
Masahiro Kato, Daiki Honma, Taka Kato
stat.MLcs.AIcs.LGarXiv:2609.11915v12026
General Cutting Planes for Bound-Propagation-Based Neural Network Verification
Huan Zhang, Shiqi Wang, Kaidi Xu +5
cs.LGcs.CRcs.CVarXiv:2208.05740v22022
Near-Optimal Reinforcement Learning with Multi-Step Transition Lookahead
Corentin Pla, Hugo Richard, Marc Abeille +1
stat.MLcs.LGarXiv:2609.11807v12026
Sparsity Regularized and Robust Mean Variance Portfolio Selection Under Ellipsoidal Uncertainty
Deniz Akkaya, Emre Can Yayla, Buse Şen +1
math.OCcs.LGstat.MLarXiv:2609.11749v12026
Plex: Towards Reliability using Pretrained Large Model Extensions
Dustin Tran, Jeremiah Liu, Michael W. Dusenberry +23
cs.LGstat.MLarXiv:2207.07411v12022
Bayesian Graph Neural Networks with Adaptive Connection Sampling
Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki +4
cs.LGstat.MLarXiv:2006.04064v32020
Generalization Analysis of Distributed Kernel-based Robust Gradient Descent Algorithms
Jun-Yi Meng, Zheng-Chu Guo, Yuan Mao
stat.MLcs.LGmath.OAarXiv:2609.11712v12026
Causal Network Inference via Group Sparse Regularization
Andrew Bolstad, Barry Van Veen, Robert Nowak
stat.MLarXiv:1106.0762v12011
Can LLMs Beat Classical Hyperparameter Optimization Algorithms? A Study on autoresearch
Fabio Ferreira, Lucca Wobbe, Arjun Krishnakumar +2
cs.LGstat.MLarXiv:2603.24647v52026
Identifiability of Nonnegative Tensor Decompositions via Positive Scattering
Haoming Wang, Ming Yuan
stat.MLcs.LGmath.COarXiv:2609.11606v12026
A distribution-free certification framework for trustworthy crash-severity prediction
Amir Rafe, Subasish Das
stat.MLcs.LGarXiv:2609.11592v12026
AdaCliP: Adaptive Clipping for Private SGD
Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu +2
cs.LGcs.CRstat.MLarXiv:1908.07643v22019
Risk-Averse Decision Making with Multi-Level Reliability Guarantees
Amirmohammad Farzaneh, Osvaldo Simeone
stat.MLcs.ITcs.LGarXiv:2609.11524v12026
Your Model Already Knows Don't Teach It, Learn to Ask It: Soft Prompting for Few-Shot Adaptation of Vision-Language Models
Gautam Rajendrakumar Gare, Siyi Li, Hewei Wang +5
cs.CVcs.AIcs.LGarXiv:2609.11310v12026
Improving the Sensitivity of Gravitational Wave Detection with Weighted Conformal Prediction
Ann-Kristin Malz, Gregory Ashton, Nicolo Colombo
gr-qccs.LGstat.MLarXiv:2609.11401v12026
A Hilbert-Valued Functional Decomposition Framework for Explaining Time-Dependent Outputs
Sophie Hanna Langbein, Niklas Koenen, Marvin N. Wright +1
stat.MLcs.LGarXiv:2609.11295v12026
On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression
Denny Wu, Ji Xu
stat.MLcs.LGmath.STarXiv:2006.05800v42020
Black-box $α$-divergence Minimization
José Miguel Hernández-Lobato, Yingzhen Li, Mark Rowland +3
stat.MLarXiv:1511.03243v32015
Rethinking the Hyperparameters for Fine-tuning
Hao Li, Pratik Chaudhari, Hao Yang +4
cs.CVcs.LGstat.MLarXiv:2002.11770v12020
Bayesian GAN
Yunus Saatchi, Andrew Gordon Wilson
stat.MLcs.AIcs.CVarXiv:1705.09558v32017
Weighted Empirical Risk Minimization for Machine Learning under Long-Range Dependence: Exact Pathwise Rates and Learning-Error Geometry
Elina Moldavskaya
stat.MLcs.LGarXiv:2609.10767v12026
Streaming Graph Neural Networks via Continual Learning
Junshan Wang, Guojie Song, Yi Wu +1
cs.LGcs.SIstat.MLarXiv:2009.10951v22020
Mind the duality gap: safer rules for the Lasso
Olivier Fercoq, Alexandre Gramfort, Joseph Salmon
stat.MLcs.LGmath.OCarXiv:1505.03410v32015
A Quantum-Inspired Dequantization Method for Diagonally Weighted Matrix Functions: Application to Learning with Optimized Random Features
Natsuto Isogai, Mio Murao, Hayata Yamasaki
quant-phcs.LGstat.MLarXiv:2609.10729v12026
Multi-agent Reinforcement Learning for Networked System Control
Tianshu Chu, Sandeep Chinchali, Sachin Katti
cs.LGstat.MLarXiv:2004.01339v22020
Probabilistic coherence and proper scoring rules
Joel Predd, Robert Seiringer, Elliott H. Lieb +3
stat.MLarXiv:0710.3183v12007
Black-Box Membership Inference via Word-Level Probability Estimation
Shengjie Niu, Yeheng Ge, Jian Huang
cs.CRcs.LGstat.MLarXiv:2609.10611v12026
V-Learning -- A Simple, Efficient, Decentralized Algorithm for Multiagent RL
Chi Jin, Qinghua Liu, Yuanhao Wang +1
cs.LGcs.AIcs.GTarXiv:2110.14555v12021
Supply Chain Analytics: A Data-Driven Approach
Elioth Sanabria
math.OCcs.LGstat.MLarXiv:2609.10563v12026
Summaries:한국어
A General End-to-end Diagnosis Framework for Manufacturing Systems
Ye Yuan, Guijun Ma, Cheng Cheng +4
cs.LGeess.SPstat.MLarXiv:1901.02057v22018
General Quantification of Covariate and Concept Shifts
Hongbo Chen, Li Charlie Xia
cs.LGcs.AIstat.MLarXiv:2609.11918v12026
On Extended Long Short-term Memory and Dependent Bidirectional Recurrent Neural Network
Yuanhang Su, C. -C. Jay Kuo
cs.LGcs.CLcs.NEarXiv:1803.01686v52018
Prediction of Compression Index of Fine-Grained Soils Using a Gene Expression Programming Model
Danial Mohammadzadeh, Seyed-Farzan Kazemi, Amir Mosavi +2
stat.APcs.LGcs.NEarXiv:1907.04913v12019
Typilus: Neural Type Hints
Miltiadis Allamanis, Earl T. Barr, Soline Ducousso +1
cs.PLcs.LGstat.MLarXiv:2004.10657v12020
Combining data assimilation and machine learning to infer unresolved scale parametrisation
Julien Brajard, Alberto Carrassi, Marc Bocquet +1
physics.comp-phstat.MLarXiv:2009.04318v22020
Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning
Gang Niu, Marthinus Christoffel du Plessis, Tomoya Sakai +2
cs.LGstat.MLarXiv:1603.03130v32016
Bayesian Learning for Neural Networks: an algorithmic survey
Martin Magris, Alexandros Iosifidis
stat.MLcs.LGarXiv:2211.11865v42022
Improving the Accuracy of Global Forecasting Models using Time Series Data Augmentation
Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu +2
cs.LGcs.AIstat.MLarXiv:2008.02663v12020
RDDMPI: Residual Denoising Diffusion Model for Probabilistic Multivariate Time Series Imputation
Ramiro Valdes Jara, David Chapman, Adam Meyers
cs.LGstat.MLarXiv:2609.11648v12026
Observational Overfitting in Reinforcement Learning
Xingyou Song, Yiding Jiang, Stephen Tu +2
cs.LGcs.AIstat.MLarXiv:1912.02975v22019
Predicting with Confidence on Unseen Distributions
Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi +2
cs.LGcs.CVstat.MLarXiv:2107.03315v22021
Free-riders in Federated Learning: Attacks and Defenses
Jierui Lin, Min Du, Jian Liu
cs.LGcs.CRstat.MLarXiv:1911.12560v12019
The autofeat Python Library for Automated Feature Engineering and Selection
Franziska Horn, Robert Pack, Michael Rieger
cs.LGstat.MLarXiv:1901.07329v42019
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization
Yuxin Chen, Yuejie Chi, Jianqing Fan +2
stat.MLcs.ITcs.LGarXiv:1902.07698v22019
Sharper bounds for uniformly stable algorithms
Olivier Bousquet, Yegor Klochkov, Nikita Zhivotovskiy
cs.LGmath.PRstat.MLarXiv:1910.07833v22019
When Explanations Lie: Why Many Modified BP Attributions Fail
Leon Sixt, Maximilian Granz, Tim Landgraf
cs.LGstat.MLarXiv:1912.09818v72019
Modern Hopfield Networks and Attention for Immune Repertoire Classification
Michael Widrich, Bernhard Schäfl, Hubert Ramsauer +8
cs.LGq-bio.BMstat.MLarXiv:2007.13505v12020
Hierarchical Clustering Can Jointly Satisfy Richness, Consistency, and Scale Invariance
Daichi Kuroda, Maximilien Dreveton, Matthias Grossglauser +1
cs.LGstat.MEstat.MLarXiv:2609.11173v12026
Large-Scale Traffic Signal Control Using a Novel Multi-Agent Reinforcement Learning
Xiaoqiang Wang, Liangjun Ke, Zhimin Qiao +1
cs.LGcs.MAstat.MLarXiv:1908.03761v22019
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
Binghui Wang, Ang Li, Hai Li +1
cs.LGstat.MLarXiv:2012.04187v12020

Machine Learning (stat)

Ensemble Methods as a Defense to Adversarial Perturbations Against Deep Neural Networks

IQP Born Machines under Data-dependent and Agnostic Initialization Strategies

Sharp Bounds on the Approximation Rates, Metric Entropy, and $n$-widths of Shallow Neural Networks

Particle Filter Networks with Application to Visual Localization

DeepHeart: Semi-Supervised Sequence Learning for Cardiovascular Risk Prediction

Dynamic Pricing in High-dimensions

Evaluating Reinforcement Learning Algorithms in Observational Health Settings

KVCOMM: Online Cross-context KV-cache Communication for Efficient LLM-based Multi-agent Systems

MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

General Cutting Planes for Bound-Propagation-Based Neural Network Verification

Near-Optimal Reinforcement Learning with Multi-Step Transition Lookahead

Sparsity Regularized and Robust Mean Variance Portfolio Selection Under Ellipsoidal Uncertainty

Plex: Towards Reliability using Pretrained Large Model Extensions

Bayesian Graph Neural Networks with Adaptive Connection Sampling

Generalization Analysis of Distributed Kernel-based Robust Gradient Descent Algorithms

Causal Network Inference via Group Sparse Regularization

Can LLMs Beat Classical Hyperparameter Optimization Algorithms? A Study on autoresearch

Identifiability of Nonnegative Tensor Decompositions via Positive Scattering

A distribution-free certification framework for trustworthy crash-severity prediction

AdaCliP: Adaptive Clipping for Private SGD

Risk-Averse Decision Making with Multi-Level Reliability Guarantees

Your Model Already Knows Don't Teach It, Learn to Ask It: Soft Prompting for Few-Shot Adaptation of Vision-Language Models

Improving the Sensitivity of Gravitational Wave Detection with Weighted Conformal Prediction

A Hilbert-Valued Functional Decomposition Framework for Explaining Time-Dependent Outputs

On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression

Black-box $α$-divergence Minimization

Rethinking the Hyperparameters for Fine-tuning

Bayesian GAN

Weighted Empirical Risk Minimization for Machine Learning under Long-Range Dependence: Exact Pathwise Rates and Learning-Error Geometry

Streaming Graph Neural Networks via Continual Learning

Mind the duality gap: safer rules for the Lasso

A Quantum-Inspired Dequantization Method for Diagonally Weighted Matrix Functions: Application to Learning with Optimized Random Features

Multi-agent Reinforcement Learning for Networked System Control

Probabilistic coherence and proper scoring rules

Black-Box Membership Inference via Word-Level Probability Estimation

V-Learning -- A Simple, Efficient, Decentralized Algorithm for Multiagent RL

Supply Chain Analytics: A Data-Driven Approach

A General End-to-end Diagnosis Framework for Manufacturing Systems

General Quantification of Covariate and Concept Shifts

On Extended Long Short-term Memory and Dependent Bidirectional Recurrent Neural Network

Prediction of Compression Index of Fine-Grained Soils Using a Gene Expression Programming Model

Typilus: Neural Type Hints

Combining data assimilation and machine learning to infer unresolved scale parametrisation

Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning

Bayesian Learning for Neural Networks: an algorithmic survey

Improving the Accuracy of Global Forecasting Models using Time Series Data Augmentation

RDDMPI: Residual Denoising Diffusion Model for Probabilistic Multivariate Time Series Imputation

Observational Overfitting in Reinforcement Learning

Predicting with Confidence on Unseen Distributions

Free-riders in Federated Learning: Attacks and Defenses

The autofeat Python Library for Automated Feature Engineering and Selection

Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization

Sharper bounds for uniformly stable algorithms

When Explanations Lie: Why Many Modified BP Attributions Fail

Modern Hopfield Networks and Attention for Immune Repertoire Classification

Hierarchical Clustering Can Jointly Satisfy Richness, Consistency, and Scale Invariance

Large-Scale Traffic Signal Control Using a Novel Multi-Agent Reinforcement Learning

GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs