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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6,961 to 7,020 of 9,718

Rapid Prediction of Electron-Ionization Mass Spectrometry using Neural Networks
Jennifer N. Wei, David Belanger, Ryan P. Adams +1
physics.chem-phstat.MLarXiv:1811.08545v22018
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Alon Brutzkus, Amir Globerson
cs.LGmath.OCstat.MLarXiv:1702.07966v12017
Sparse and Imperceivable Adversarial Attacks
Francesco Croce, Matthias Hein
cs.LGcs.CRcs.CVarXiv:1909.05040v12019
Beyond Discrepancy: Oracle Drift in Nonstationary Weighted Risk Minimization
Tobias Brock, Thomas Nagler
math.STstat.MLarXiv:2610.13598v12026
How Do Transformers Learn Topic Structure: Towards a Mechanistic Understanding
Yuchen Li, Yuanzhi Li, Andrej Risteski
cs.LGcs.CLstat.MLarXiv:2303.04245v22023
A review on distance based time series classification
Amaia Abanda, Usue Mori, Jose A. Lozano
stat.MLcs.LGarXiv:1806.04509v12018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You, Bowen Liu, Rex Ying +2
cs.LGcs.AIstat.MLarXiv:1806.02473v32018
Generalizable Adversarial Training via Spectral Normalization
Farzan Farnia, Jesse M. Zhang, David Tse
cs.LGstat.MLarXiv:1811.07457v12018
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems
Yunseong Lee, Alberto Scolari, Byung-Gon Chun +3
cs.LGcs.DCstat.MLarXiv:1810.06115v12018
Subliminal Effects in Your Data: A General Mechanism via Log-Linearity
Ishaq Aden-Ali, Noah Golowich, Allen Liu +3
cs.LGcs.AIcs.CLarXiv:2602.04863v12026
Gaussian BROJA Partial Information Decomposition in Closed Form
Ohad Sheelo, Tal Golan, Ari Pakman
cs.ITstat.MLarXiv:2610.13464v12026
Neon2: Finding Local Minima via First-Order Oracles
Zeyuan Allen-Zhu, Yuanzhi Li
cs.LGcs.DScs.NEarXiv:1711.06673v32017
Thoracic Disease Identification and Localization with Limited Supervision
Zhe Li, Chong Wang, Mei Han +4
cs.CVstat.MLarXiv:1711.06373v62017
Machine Learning for Survival Analysis: A Survey
Ping Wang, Yan Li, Chandan K. Reddy
cs.LGstat.MLarXiv:1708.04649v12017
Stationary signal processing on graphs
Nathanaël Perraudin, Pierre Vandergheynst
cs.DSstat.APstat.MLarXiv:1601.02522v52016
Continuous Inverse Optimal Control with Locally Optimal Examples
Sergey Levine, Vladlen Koltun
cs.LGcs.AIstat.MLarXiv:1206.4617v12012
Online Control via Counterfactual Tracking
Yunzong Xu
math.OCcs.LGcs.SYarXiv:2607.13029v22026
Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model
David John Gagne, Hannah M. Christensen, Aneesh C. Subramanian +1
physics.ao-phcs.LGnlin.CDarXiv:1909.04711v12019
Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models
Jesse Engel, Matthew Hoffman, Adam Roberts
cs.LGcs.NEstat.MLarXiv:1711.05772v22017
Interpretation and Generalization of Score Matching
Siwei Lyu
cs.LGstat.MLarXiv:1205.2629v12012
When More Sampling Hurts: The Modal Ceiling and Correlation Ceiling of Test-Time Scaling
Yong Yi Bay, Kathleen A. Yearick
cs.LGcs.AIcs.CLarXiv:2606.28661v12026
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable
Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal +2
cs.LGstat.MLarXiv:1610.09512v22016
Poly-time universality and limitations of deep learning
Emmanuel Abbe, Colin Sandon
cs.LGcs.CCcs.ITarXiv:2001.02992v12020
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability
Alex Damian, Eshaan Nichani, Jason D. Lee
cs.LGcs.ITmath.OCarXiv:2209.15594v22022
SurvivalPFN: Amortizing Survival Prediction via In-Context Bayesian Inference
Shi-ang Qi, Vahid Balazadeh, Michael Cooper +2
cs.LGstat.MLarXiv:2605.15488v12026
Graph Structure of Neural Networks
Jiaxuan You, Jure Leskovec, Kaiming He +1
cs.LGcs.CVcs.SIarXiv:2007.06559v22020
Ward's Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm
Fionn Murtagh, Pierre Legendre
stat.MLcs.CVstat.AParXiv:1111.6285v22011
Straggler Mitigation in Distributed Optimization Through Data Encoding
Can Karakus, Yifan Sun, Suhas Diggavi +1
stat.MLcs.DCcs.ITarXiv:1711.04969v22017
Time Series Data Augmentation for Neural Networks by Time Warping with a Discriminative Teacher
Brian Kenji Iwana, Seiichi Uchida
cs.LGstat.MLarXiv:2004.08780v12020
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong, Zhao Song, Prateek Jain +2
cs.LGcs.DSstat.MLarXiv:1706.03175v12017
Training GANs with Optimism
Constantinos Daskalakis, Andrew Ilyas, Vasilis Syrgkanis +1
cs.LGcs.GTstat.MLarXiv:1711.00141v22017
Patent Claim Generation by Fine-Tuning OpenAI GPT-2
Jieh-Sheng Lee, Jieh Hsiang
cs.CLcs.LGstat.MLarXiv:1907.02052v12019
ATOMO: Communication-efficient Learning via Atomic Sparsification
Hongyi Wang, Scott Sievert, Zachary Charles +3
stat.MLcs.DCcs.LGarXiv:1806.04090v32018
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
Robert Peharz, Steven Lang, Antonio Vergari +6
cs.LGstat.MLarXiv:2004.06231v22020
Lossy Image Compression with Compressive Autoencoders
Lucas Theis, Wenzhe Shi, Andrew Cunningham +1
stat.MLcs.CVarXiv:1703.00395v12017
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems
Jiani Zhang, Xingjian Shi, Shenglin Zhao +1
cs.IRcs.LGcs.SIarXiv:1905.13129v12019
Disentangling factors of variation in deep representations using adversarial training
Michael Mathieu, Junbo Zhao, Pablo Sprechmann +2
cs.LGstat.MLarXiv:1611.03383v12016
Transductive Rademacher Complexity and its Applications
Ran El-Yaniv, Dmitry Pechyony
cs.LGcs.AIstat.MLarXiv:1401.3441v12014
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search
Xiangxiang Chu, Bo Zhang, Ruijun Xu
cs.LGcs.AIcs.CVarXiv:1907.01845v52019
Block-Sparse Recurrent Neural Networks
Sharan Narang, Eric Undersander, Gregory Diamos
cs.LGcs.AIstat.MLarXiv:1711.02782v12017
Deep Convolutional Neural Networks for Massive MIMO Fingerprint-Based Positioning
Joao Vieira, Erik Leitinger, Muris Sarajlic +2
stat.MLcs.ITarXiv:1708.06235v12017
Exploiting Gradients in Bayesian Inference of Expensive Simulators
Šimon Soldát, Václav Šmídl
cs.LGstat.MLarXiv:2610.12076v12026
Deep Generalized Canonical Correlation Analysis
Adrian Benton, Huda Khayrallah, Biman Gujral +3
cs.LGcs.AIstat.MLarXiv:1702.02519v22017
The ALAMO approach to machine learning
Zachary T. Wilson, Nikolaos V. Sahinidis
cs.LGstat.MLarXiv:1705.10918v12017
Why Heavy-Tailed Weight Spectra Predict Model Quality
Joseph Wilson, Chris van der Heide, Liam Hodgkinson +3
stat.MLcs.LGarXiv:2610.13123v12026
Subtask Gated Networks for Non-Intrusive Load Monitoring
Changho Shin, Sunghwan Joo, Jaeryun Yim +3
cs.LGstat.APstat.MLarXiv:1811.06692v12018
Robust Optimization for Fairness with Noisy Protected Groups
Serena Wang, Wenshuo Guo, Harikrishna Narasimhan +3
cs.LGstat.MLarXiv:2002.09343v32020
Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space
Jiechao Xiong, Qing Wang, Zhuoran Yang +7
cs.LGcs.AIstat.MLarXiv:1810.06394v12018
Neural Thompson Sampling
Weitong Zhang, Dongruo Zhou, Lihong Li +1
cs.LGstat.MLarXiv:2010.00827v22020
Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising
Junwei Pan, Jian Xu, Alfonso Lobos Ruiz +4
cs.LGstat.MLarXiv:1806.03514v22018
Markov Decision Processes with Continuous Side Information
Aditya Modi, Nan Jiang, Satinder Singh +1
stat.MLcs.AIcs.LGarXiv:1711.05726v12017
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
Fast global convergence of gradient methods for high-dimensional statistical recovery
Alekh Agarwal, Sahand N. Negahban, Martin J. Wainwright
stat.MLcs.ITarXiv:1104.4824v32011
Representation Learning for Online and Offline RL in Low-rank MDPs
Masatoshi Uehara, Xuezhou Zhang, Wen Sun
cs.LGcs.AIstat.MLarXiv:2110.04652v32021
The Exceedance Design Effect: Effective Sample Size for Thresholds under Clustering
Adam Noonan
stat.MLcs.LGarXiv:2608.21262v12026
Bayesian Learning for Neural Networks: an algorithmic survey
Martin Magris, Alexandros Iosifidis
stat.MLcs.LGarXiv:2211.11865v42022
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD
Zeyuan Allen-Zhu
cs.LGcs.DSmath.OCarXiv:1801.02982v32018
ADD for Multi-Bit Image Watermarking
An Luo, Jie Ding
stat.MLcs.AIcs.LGarXiv:2604.11491v12026
Hierarchical modeling of molecular energies using a deep neural network
Nicholas Lubbers, Justin S. Smith, Kipton Barros
stat.MLphysics.chem-pharXiv:1710.00017v12017
The probability flow ODE is provably fast
Sitan Chen, Sinho Chewi, Holden Lee +3
cs.LGmath.STstat.MLarXiv:2305.11798v12023

Machine Learning (stat)

Rapid Prediction of Electron-Ionization Mass Spectrometry using Neural Networks

Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs

Sparse and Imperceivable Adversarial Attacks

Beyond Discrepancy: Oracle Drift in Nonstationary Weighted Risk Minimization

How Do Transformers Learn Topic Structure: Towards a Mechanistic Understanding

A review on distance based time series classification

Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

Generalizable Adversarial Training via Spectral Normalization

PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems

Subliminal Effects in Your Data: A General Mechanism via Log-Linearity

Gaussian BROJA Partial Information Decomposition in Closed Form

Neon2: Finding Local Minima via First-Order Oracles

Thoracic Disease Identification and Localization with Limited Supervision

Machine Learning for Survival Analysis: A Survey

Stationary signal processing on graphs

Continuous Inverse Optimal Control with Locally Optimal Examples

Online Control via Counterfactual Tracking

Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model

Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models

Interpretation and Generalization of Score Matching

When More Sampling Hurts: The Modal Ceiling and Correlation Ceiling of Test-Time Scaling

Contextual Decision Processes with Low Bellman Rank are PAC-Learnable

Poly-time universality and limitations of deep learning

Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability

SurvivalPFN: Amortizing Survival Prediction via In-Context Bayesian Inference

Graph Structure of Neural Networks

Ward's Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm

Straggler Mitigation in Distributed Optimization Through Data Encoding

Time Series Data Augmentation for Neural Networks by Time Warping with a Discriminative Teacher

Recovery Guarantees for One-hidden-layer Neural Networks

Training GANs with Optimism

Patent Claim Generation by Fine-Tuning OpenAI GPT-2

ATOMO: Communication-efficient Learning via Atomic Sparsification

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

Lossy Image Compression with Compressive Autoencoders

STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems

Disentangling factors of variation in deep representations using adversarial training

Transductive Rademacher Complexity and its Applications

FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search

Block-Sparse Recurrent Neural Networks

Deep Convolutional Neural Networks for Massive MIMO Fingerprint-Based Positioning

Exploiting Gradients in Bayesian Inference of Expensive Simulators

Deep Generalized Canonical Correlation Analysis

The ALAMO approach to machine learning

Why Heavy-Tailed Weight Spectra Predict Model Quality

Subtask Gated Networks for Non-Intrusive Load Monitoring

Robust Optimization for Fairness with Noisy Protected Groups

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space

Neural Thompson Sampling

Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising

Markov Decision Processes with Continuous Side Information

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

Fast global convergence of gradient methods for high-dimensional statistical recovery

Representation Learning for Online and Offline RL in Low-rank MDPs

The Exceedance Design Effect: Effective Sample Size for Thresholds under Clustering

Bayesian Learning for Neural Networks: an algorithmic survey

How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD

ADD for Multi-Bit Image Watermarking

Hierarchical modeling of molecular energies using a deep neural network

The probability flow ODE is provably fast