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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481 to 540 of 6,784

Likelihood-free inference with nuisance parameters through normalizing flows
Phil Assheton
stat.MEcs.LGstat.MLarXiv:2609.10534v12026
Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction
Mingyuan Zhou
stat.MLcs.SIarXiv:1501.06218v22015
Quantum-Inspired Support Vector Machine
Chen Ding, Tian-Yi Bao, He-Liang Huang
cs.LGcs.CCquant-pharXiv:1906.08902v52019
Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity
Amirhossein Reisizadeh, Isidoros Tziotis, Hamed Hassani +2
cs.LGcs.DCstat.MLarXiv:2012.14453v12020
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT
Philipp Seeböck, José Ignacio Orlando, Thomas Schlegl +5
eess.IVcs.CVcs.LGarXiv:1905.12806v12019
Generalization in Generation: A closer look at Exposure Bias
Florian Schmidt
cs.LGcs.CLstat.MLarXiv:1910.00292v22019
Data Stream Clustering: A Review
Alaettin Zubaroğlu, Volkan Atalay
cs.LGcs.AIcs.DBarXiv:2007.10781v12020
An expert system for detecting automobile insurance fraud using social network analysis
Lovro Šubelj, Štefan Furlan, Marko Bajec
cs.AIcs.SIphysics.soc-pharXiv:1104.3904v12011
Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network
Sheng Wan, Chen Gong, Ping Zhong +3
cs.LGcs.CVeess.IVarXiv:1909.11953v12019
Deep Generative Models for Distribution-Preserving Lossy Compression
Michael Tschannen, Eirikur Agustsson, Mario Lucic
cs.LGstat.MLarXiv:1805.11057v22018
A Unifying Perspective on Probabilities as Model Predictions
Benedikt Höltgen
stat.MLcs.CYcs.LGarXiv:2609.09855v12026
Deep learning via LSTM models for COVID-19 infection forecasting in India
Rohitash Chandra, Ayush Jain, Divyanshu Singh Chauhan
cs.LGcs.AIstat.AParXiv:2101.11881v22021
Likelihood-free inference with emulator networks
Jan-Matthis Lueckmann, Giacomo Bassetto, Theofanis Karaletsos +1
stat.MLcs.LGarXiv:1805.09294v22018
Causal Inference for Time series Analysis: Problems, Methods and Evaluation
Raha Moraffah, Paras Sheth, Mansooreh Karami +5
cs.LGstat.MLarXiv:2102.05829v12021
Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise
Michał Koziarski, Michał Woźniak, Bartosz Krawczyk
cs.LGstat.MLarXiv:2004.03406v12020
Optimal Value Inference for Reinforcement Learning
Nan Lu, Ethan Lee, James M. Robins +2
stat.MLcs.LGstat.MEarXiv:2609.09981v12026
Why Learning Rediscovers the Closed-Form Diagonal Regularizer
Jeahn Han, Pyojin Kim
stat.MLcs.LGcs.ROarXiv:2609.09656v12026
Deep Hyperspherical Learning
Weiyang Liu, Yan-Ming Zhang, Xingguo Li +4
cs.LGcs.CVstat.MLarXiv:1711.03189v52017
Benchmarking Attribution Methods with Relative Feature Importance
Mengjiao Yang, Been Kim
cs.LGstat.MLarXiv:1907.09701v22019
Learning Relevant Features of Data with Multi-scale Tensor Networks
E. M. Stoudenmire
stat.MLcond-mat.stat-mechcond-mat.str-elarXiv:1801.00315v12017
A General Pipeline for 3D Detection of Vehicles
Xinxin Du, Marcelo H. Ang, Sertac Karaman +1
cs.CVeess.IVstat.MLarXiv:1803.00387v12018
Towards More Practical Adversarial Attacks on Graph Neural Networks
Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei
cs.LGstat.MLarXiv:2006.05057v32020
Distillation of Synthetic Data for Time Series Foundation Models
Niloy Biswas, Noureddine El Karoui
stat.MLcs.LGarXiv:2609.09586v12026
Oracle Complexity of Stochastic Fixed-Point Equations with Nonexpansive Maps
Jelena Diakonikolas, Cristóbal Guzmán, David Martínez-Rubio
math.OCcs.DScs.LGarXiv:2609.09524v12026
2D Car Detection in Radar Data with PointNets
Andreas Danzer, Thomas Griebel, Martin Bach +1
cs.CVcs.LGstat.MLarXiv:1904.08414v32019
Direct Uncertainty Prediction for Medical Second Opinions
Maithra Raghu, Katy Blumer, Rory Sayres +4
cs.LGstat.MLarXiv:1807.01771v42018
Towards Imperceptible and Robust Adversarial Example Attacks against Neural Networks
Bo Luo, Yannan Liu, Lingxiao Wei +1
cs.LGcs.CRstat.MLarXiv:1801.04693v12018
DeepTravel: a Neural Network Based Travel Time Estimation Model with Auxiliary Supervision
Hanyuan Zhang, Hao Wu, Weiwei Sun +1
cs.LGcs.CVstat.MLarXiv:1802.02147v12018
Gaussian Approximation for Multivariate Martingale Sums from Uniformly Ergodic Markov Chains
Yixuan Zhang, Qiaomin Xie
math.PRcs.LGstat.MLarXiv:2609.09480v12026
Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale
Stephen H. Bach, Daniel Rodriguez, Yintao Liu +10
cs.LGstat.MLarXiv:1812.00417v22018
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom +2
cs.CVcs.LGstat.MLarXiv:2005.11295v12020
Mode Coverage in Normalizing Flow Boltzmann Generators via Log-Ratio Variation
Qi Feng, Rongjie Lai, Di Qi +1
stat.MLcs.LGarXiv:2609.09473v12026
MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra
Balázs Csanád Csáji, Bálint Horváth
math.STcs.LGeess.SParXiv:2609.09436v12026
Globally-Robust Neural Networks
Klas Leino, Zifan Wang, Matt Fredrikson
cs.LGcs.CRstat.MLarXiv:2102.08452v22021
T2FSNN: Deep Spiking Neural Networks with Time-to-first-spike Coding
Seongsik Park, Seijoon Kim, Byunggook Na +1
cs.NEcs.LGstat.MLarXiv:2003.11741v12020
Multiple Source Adaptation and the Renyi Divergence
Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh
cs.LGstat.MLarXiv:1205.2628v12012
Neural Adaptive Sequential Monte Carlo
Shixiang Gu, Zoubin Ghahramani, Richard E. Turner
cs.LGstat.MLarXiv:1506.03338v32015
A positive resolution of the gap-entropy conjecture
P. M. Aronow, Nathan Kallus, Patrick Lopatto
cs.LGstat.MLarXiv:2609.10529v12026
A Subsampled Davis-Kahan Bound for Large-Scale Eigenspace Estimation
Huan Qing
stat.MLcs.LGstat.MEarXiv:2609.09211v12026
Efficient Dataset Distillation Using Random Feature Approximation
Noel Loo, Ramin Hasani, Alexander Amini +1
cs.LGcs.AIcs.NEarXiv:2210.12067v12022
Tensor Network Moral Graph Recovery of Discrete Probability Distributions
Á. Troyano Olivas, Chi-Hang Fred Fung, Hans H. Brunner +2
stat.MLcs.ITcs.LGarXiv:2609.09258v12026
CAST: Canonical Approximate Schur Tree for Approximate Cholesky on Graphs
Meher Chaitanya, Cameron Musco, Aristides Gionis
stat.MLcs.LGmath.NAarXiv:2609.09255v12026
Quantile Regression Under Memory Constraint
Xi Chen, Weidong Liu, Yichen Zhang
stat.MEecon.EMstat.MLarXiv:1810.08264v12018
VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification
Zhibin Lu, Pan Du, Jian-Yun Nie
cs.CLcs.LGstat.MLarXiv:2004.05707v12020
Stacking Models for Nearly Optimal Link Prediction in Complex Networks
Amir Ghasemian, Homa Hosseinmardi, Aram Galstyan +2
stat.MLcs.LGcs.SIarXiv:1909.07578v12019
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
Jesse Farebrother, Jordi Orbay, Quan Vuong +9
cs.LGcs.AIstat.MLarXiv:2403.03950v12024
Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm
Pascal Germain, Alexandre Lacasse, François Laviolette +2
stat.MLcs.LGarXiv:1503.08329v22015
Scalable Constrained Bayesian Optimization
David Eriksson, Matthias Poloczek
cs.LGcs.AIstat.MLarXiv:2002.08526v32020
An Exponential Deterministic--Randomized Gap in ERM-Oracle Complexity for Thresholds on an Unknown Order
Xuan Li
cs.LGstat.MLarXiv:2609.10196v12026
The Price of Sparsity: Sufficient Conditions for Sparse Recovery using Sparse and Sparsified Measurements
Youssef Chaabouni, David Gamarnik
stat.MLcs.ITcs.LGarXiv:2509.01809v22025
Improving Adversarial Robustness of Ensembles with Diversity Training
Sanjay Kariyappa, Moinuddin K. Qureshi
stat.MLcs.LGarXiv:1901.09981v12019
Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework
Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt +6
cs.LGcs.AIstat.MLarXiv:2006.13365v52020
SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics
Emmanuel Abbe, Enric Boix-Adsera, Theodor Misiakiewicz
cs.LGstat.MLarXiv:2302.11055v22023
Policy Gradient for Coherent Risk Measures
Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh +1
cs.AIcs.LGstat.MLarXiv:1502.03919v22015
ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots
Michael Ahn, Henry Zhu, Kristian Hartikainen +4
cs.ROcs.LGstat.MLarXiv:1909.11639v32019
Accountable and uncertainty-aware evaluation of sensor-based AI under distribution shift: devices, subjects, and nearly three years underground
Benny Platte, Rico Thomanek, Christian Roschke +1
cs.LGstat.MEstat.MLarXiv:2609.09257v12026
Classical Statistics and Statistical Learning in Imaging Neuroscience
Danilo Bzdok
stat.MLq-bio.NCarXiv:1603.01857v22016
Predicting University Students' Academic Success and Major using Random Forests
Cédric Beaulac, Jeffrey S. Rosenthal
stat.MLcs.LGarXiv:1802.03418v32018
Differentiable Graph Module (DGM) for Graph Convolutional Networks
Anees Kazi, Luca Cosmo, Seyed-Ahmad Ahmadi +2
cs.LGstat.MLarXiv:2002.04999v42020
Straggler Mitigation in Distributed Optimization Through Data Encoding
Can Karakus, Yifan Sun, Suhas Diggavi +1
stat.MLcs.DCcs.ITarXiv:1711.04969v22017

Machine Learning (stat)

Likelihood-free inference with nuisance parameters through normalizing flows

Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction

Quantum-Inspired Support Vector Machine

Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity

Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT

Generalization in Generation: A closer look at Exposure Bias

Data Stream Clustering: A Review

An expert system for detecting automobile insurance fraud using social network analysis

Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network

Deep Generative Models for Distribution-Preserving Lossy Compression

A Unifying Perspective on Probabilities as Model Predictions

Deep learning via LSTM models for COVID-19 infection forecasting in India

Likelihood-free inference with emulator networks

Causal Inference for Time series Analysis: Problems, Methods and Evaluation

Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise

Optimal Value Inference for Reinforcement Learning

Why Learning Rediscovers the Closed-Form Diagonal Regularizer

Deep Hyperspherical Learning

Benchmarking Attribution Methods with Relative Feature Importance

Learning Relevant Features of Data with Multi-scale Tensor Networks

A General Pipeline for 3D Detection of Vehicles

Towards More Practical Adversarial Attacks on Graph Neural Networks

Distillation of Synthetic Data for Time Series Foundation Models

Oracle Complexity of Stochastic Fixed-Point Equations with Nonexpansive Maps

2D Car Detection in Radar Data with PointNets

Direct Uncertainty Prediction for Medical Second Opinions

Towards Imperceptible and Robust Adversarial Example Attacks against Neural Networks

DeepTravel: a Neural Network Based Travel Time Estimation Model with Auxiliary Supervision

Gaussian Approximation for Multivariate Martingale Sums from Uniformly Ergodic Markov Chains

Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale

From ImageNet to Image Classification: Contextualizing Progress on Benchmarks

Mode Coverage in Normalizing Flow Boltzmann Generators via Log-Ratio Variation

MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra

Globally-Robust Neural Networks

T2FSNN: Deep Spiking Neural Networks with Time-to-first-spike Coding

Multiple Source Adaptation and the Renyi Divergence

Neural Adaptive Sequential Monte Carlo

A positive resolution of the gap-entropy conjecture

A Subsampled Davis-Kahan Bound for Large-Scale Eigenspace Estimation

Efficient Dataset Distillation Using Random Feature Approximation

Tensor Network Moral Graph Recovery of Discrete Probability Distributions

CAST: Canonical Approximate Schur Tree for Approximate Cholesky on Graphs

Quantile Regression Under Memory Constraint

VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification

Stacking Models for Nearly Optimal Link Prediction in Complex Networks

Stop Regressing: Training Value Functions via Classification for Scalable Deep RL

Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm

Scalable Constrained Bayesian Optimization

An Exponential Deterministic--Randomized Gap in ERM-Oracle Complexity for Thresholds on an Unknown Order

The Price of Sparsity: Sufficient Conditions for Sparse Recovery using Sparse and Sparsified Measurements

Improving Adversarial Robustness of Ensembles with Diversity Training

Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework

SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics

Policy Gradient for Coherent Risk Measures

ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots

Accountable and uncertainty-aware evaluation of sensor-based AI under distribution shift: devices, subjects, and nearly three years underground

Classical Statistics and Statistical Learning in Imaging Neuroscience

Predicting University Students' Academic Success and Major using Random Forests

Differentiable Graph Module (DGM) for Graph Convolutional Networks

Straggler Mitigation in Distributed Optimization Through Data Encoding