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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4,861 to 4,920 of 6,780

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Ekagra Ranjan, Soumya Sanyal, Partha Pratim Talukdar
cs.LGstat.MLarXiv:1911.07979v32019
Understanding and Robustifying Differentiable Architecture Search
Arber Zela, Thomas Elsken, Tonmoy Saikia +3
cs.LGcs.AIcs.CVarXiv:1909.09656v22019
Data Augmentation Can Improve Robustness
Sylvestre-Alvise Rebuffi, Sven Gowal, Dan A. Calian +3
cs.CVcs.LGstat.MLarXiv:2111.05328v12021
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning
Matthias Feurer, Katharina Eggensperger, Stefan Falkner +2
cs.LGstat.MLarXiv:2007.04074v32020
Batch Bayesian Optimization via Local Penalization
Javier González, Zhenwen Dai, Philipp Hennig +1
stat.MLarXiv:1505.08052v42015
Predicting Station-level Hourly Demands in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approach
Lei Lin, Zhengbing He, Srinivas Peeta
stat.MLcs.LGarXiv:1712.04997v22017
Spectral Norm Regularization for Improving the Generalizability of Deep Learning
Yuichi Yoshida, Takeru Miyato
stat.MLcs.LGarXiv:1705.10941v12017
Exponentially Weighted Moving Average Charts for Detecting Concept Drift
Gordon J. Ross, Niall M. Adams, Dimitris K. Tasoulis +1
stat.MLcs.LGstat.AParXiv:1212.6018v12012
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data
Maximilian Karl, Maximilian Soelch, Justin Bayer +1
stat.MLcs.LGeess.SYarXiv:1605.06432v32016
A Survey of Deep Meta-Learning
Mike Huisman, Jan N. van Rijn, Aske Plaat
cs.LGcs.AIstat.MLarXiv:2010.03522v22020
High Dimensional Bayesian Optimisation and Bandits via Additive Models
Kirthevasan Kandasamy, Jeff Schneider, Barnabas Poczos
stat.MLcs.LGarXiv:1503.01673v32015
Identity Matters in Deep Learning
Moritz Hardt, Tengyu Ma
cs.LGcs.NEstat.MLarXiv:1611.04231v32016
Beyond Parity: Fairness Objectives for Collaborative Filtering
Sirui Yao, Bert Huang
cs.IRcs.AIcs.LGarXiv:1705.08804v22017
High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm
Alain Durmus, Eric Moulines
math.STstat.MEstat.MLarXiv:1605.01559v42016
All-but-the-Top: Simple and Effective Postprocessing for Word Representations
Jiaqi Mu, Suma Bhat, Pramod Viswanath
cs.CLstat.MLarXiv:1702.01417v22017
Programmatically Interpretable Reinforcement Learning
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh +2
cs.LGcs.AIcs.PLarXiv:1804.02477v32018
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
Colin White, Willie Neiswanger, Yash Savani
cs.LGcs.NEstat.MLarXiv:1910.11858v32019
Neural Lyapunov Control
Ya-Chien Chang, Nima Roohi, Sicun Gao
cs.LGcs.NEcs.ROarXiv:2005.00611v42020
Self-Supervised Representation Learning: Introduction, Advances and Challenges
Linus Ericsson, Henry Gouk, Chen Change Loy +1
cs.LGcs.CVstat.MLarXiv:2110.09327v12021
Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes
Xianyan Jia, Shutao Song, Wei He +11
cs.LGcs.DCstat.MLarXiv:1807.11205v12018
Heterogeneous Graph Neural Networks for Malicious Account Detection
Ziqi Liu, Chaochao Chen, Xinxing Yang +3
cs.LGcs.CRstat.MLarXiv:2002.12307v12020
DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs
Ali Sadeghian, Mohammadreza Armandpour, Patrick Ding +1
cs.LGcs.LOstat.MLarXiv:1911.00055v12019
Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning
Oren Z. Kraus, Lei Jimmy Ba, Brendan Frey
cs.CVq-bio.SCstat.MLarXiv:1511.05286v12015
StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks
Hirokazu Kameoka, Takuhiro Kaneko, Kou Tanaka +1
cs.SDcs.LGeess.ASarXiv:1806.02169v22018
A Reliable Effective Terascale Linear Learning System
Alekh Agarwal, Olivier Chapelle, Miroslav Dudik +1
cs.LGstat.MLarXiv:1110.4198v32011
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning
Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi
stat.MLcs.LGarXiv:2007.02923v12020
Anomaly Detection using One-Class Neural Networks
Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
cs.LGcs.NEstat.MLarXiv:1802.06360v22018
Interpretability of machine learning based prediction models in healthcare
Gregor Stiglic, Primoz Kocbek, Nino Fijacko +3
cs.LGstat.MLarXiv:2002.08596v22020
High-Quality Self-Supervised Deep Image Denoising
Samuli Laine, Tero Karras, Jaakko Lehtinen +1
cs.LGcs.CVcs.NEarXiv:1901.10277v32019
Graph Clustering with Graph Neural Networks
Anton Tsitsulin, John Palowitch, Bryan Perozzi +1
cs.LGcs.SIstat.MLarXiv:2006.16904v32020
TIGRESS: Trustful Inference of Gene REgulation using Stability Selection
Anne-Claire Haury, Fantine Mordelet, Paola Vera-Licona +1
stat.MLq-bio.QMarXiv:1205.1181v12012
Character-Level Language Modeling with Deeper Self-Attention
Rami Al-Rfou, Dokook Choe, Noah Constant +2
cs.CLcs.AIcs.LGarXiv:1808.04444v22018
The Lottery Ticket Hypothesis for Pre-trained BERT Networks
Tianlong Chen, Jonathan Frankle, Shiyu Chang +4
cs.LGcs.CLcs.NEarXiv:2007.12223v22020
Classification-Based Anomaly Detection for General Data
Liron Bergman, Yedid Hoshen
cs.LGcs.CVstat.MLarXiv:2005.02359v12020
Gromov-Monge Flow Matching for Equivariant Graph Generation
Moritz Piening, Christian Wald
cs.LGmath.OCstat.MLarXiv:2608.26961v12026
Safe, Efficient, and Comfortable Velocity Control based on Reinforcement Learning for Autonomous Driving
Meixin Zhu, Yinhai Wang, Ziyuan Pu +3
cs.LGcs.AIcs.ROarXiv:1902.00089v22019
Does label smoothing mitigate label noise?
Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon +1
cs.LGstat.MLarXiv:2003.02819v12020
Information-Theoretic Considerations in Batch Reinforcement Learning
Jinglin Chen, Nan Jiang
cs.LGcs.AIstat.MLarXiv:1905.00360v12019
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
Hattie Zhou, Janice Lan, Rosanne Liu +1
cs.LGcs.CVstat.MLarXiv:1905.01067v42019
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction
Liang-Chieh Chen, Maxwell D. Collins, Yukun Zhu +5
cs.CVcs.LGstat.MLarXiv:1809.04184v12018
Explainable Reinforcement Learning Through a Causal Lens
Prashan Madumal, Tim Miller, Liz Sonenberg +1
cs.LGcs.AIcs.HCarXiv:1905.10958v22019
Double/Debiased/Neyman Machine Learning of Treatment Effects
Victor Chernozhukov, Denis Chetverikov, Mert Demirer +3
stat.MLstat.MEarXiv:1701.08687v12017
Modeling User Exposure in Recommendation
Dawen Liang, Laurent Charlin, James McInerney +1
stat.MLcs.IRcs.LGarXiv:1510.07025v22015
Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics
Yunbo Wang, Jianjin Zhang, Hongyu Zhu +3
cs.LGstat.MLarXiv:1811.07490v32018
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan +1
cs.LGstat.MLarXiv:1904.06387v52019
Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging
Emilie Gerardin, Gaël Chételat, Marie Chupin +9
cs.CVq-bio.NCstat.MLarXiv:1707.05961v12017
A Theory of Regularized Markov Decision Processes
Matthieu Geist, Bruno Scherrer, Olivier Pietquin
cs.LGstat.MLarXiv:1901.11275v22019
Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records
Li Huang, Dianbo Liu
cs.LGstat.MLarXiv:1903.09296v12019
Deep Air Quality Forecasting Using Hybrid Deep Learning Framework
Shengdong Du, Tianrui Li, Yan Yang +1
cs.LGstat.MLarXiv:1812.04783v32018
Quantization Networks
Jiwei Yang, Xu Shen, Jun Xing +5
cs.CVcs.LGstat.MLarXiv:1911.09464v22019
An Empirical Model of Large-Batch Training
Sam McCandlish, Jared Kaplan, Dario Amodei +1
cs.LGstat.MLarXiv:1812.06162v12018
Optimal Best Arm Identification with Fixed Confidence
Aurélien Garivier, Emilie Kaufmann
math.STcs.LGstat.MLarXiv:1602.04589v22016
Active Diffusion-Based Inference for Ill-Posed Inverse Problems under Incomplete Priors
Jitao Xu, Nobuo Sato, Yaohang Li
stat.MLcs.AIcs.LGarXiv:2608.27080v12026
Adversarial Training and Robustness for Multiple Perturbations
Florian Tramèr, Dan Boneh
cs.LGcs.CRstat.MLarXiv:1904.13000v22019
Understanding Measures of Uncertainty for Adversarial Example Detection
Lewis Smith, Yarin Gal
stat.MLcs.LGarXiv:1803.08533v12018
The Benefit of Multitask Representation Learning
Andreas Maurer, Massimiliano Pontil, Bernardino Romera-Paredes
stat.MLcs.LGarXiv:1505.06279v22015
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
Jungmin Kwon, Jeongseop Kim, Hyunseo Park +1
cs.LGstat.MLarXiv:2102.11600v32021
TRACE-CRC: Trajectory-Adaptive Conformal Risk Control for Multi-Step Channel State Information Prediction
Kiarash Rezaei, Mehdi Sattari, Javad Aliakbari +3
cs.LGstat.MLarXiv:2608.27124v12026
GANSynth: Adversarial Neural Audio Synthesis
Jesse Engel, Kumar Krishna Agrawal, Shuo Chen +3
cs.SDcs.LGeess.ASarXiv:1902.08710v22019
Learning graphs from data: A signal representation perspective
Xiaowen Dong, Dorina Thanou, Michael Rabbat +1
cs.LGcs.SIstat.MLarXiv:1806.00848v32018

Machine Learning (stat)

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

Understanding and Robustifying Differentiable Architecture Search

Data Augmentation Can Improve Robustness

Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning

Batch Bayesian Optimization via Local Penalization

Predicting Station-level Hourly Demands in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approach

Spectral Norm Regularization for Improving the Generalizability of Deep Learning

Exponentially Weighted Moving Average Charts for Detecting Concept Drift

Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data

A Survey of Deep Meta-Learning

High Dimensional Bayesian Optimisation and Bandits via Additive Models

Identity Matters in Deep Learning

Beyond Parity: Fairness Objectives for Collaborative Filtering

High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm

All-but-the-Top: Simple and Effective Postprocessing for Word Representations

Programmatically Interpretable Reinforcement Learning

BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search

Neural Lyapunov Control

Self-Supervised Representation Learning: Introduction, Advances and Challenges

Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes

Heterogeneous Graph Neural Networks for Malicious Account Detection

DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs

Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning

StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks

A Reliable Effective Terascale Linear Learning System

Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

Anomaly Detection using One-Class Neural Networks

Interpretability of machine learning based prediction models in healthcare

High-Quality Self-Supervised Deep Image Denoising

Graph Clustering with Graph Neural Networks

TIGRESS: Trustful Inference of Gene REgulation using Stability Selection

Character-Level Language Modeling with Deeper Self-Attention

The Lottery Ticket Hypothesis for Pre-trained BERT Networks

Classification-Based Anomaly Detection for General Data

Gromov-Monge Flow Matching for Equivariant Graph Generation

Safe, Efficient, and Comfortable Velocity Control based on Reinforcement Learning for Autonomous Driving

Does label smoothing mitigate label noise?

Information-Theoretic Considerations in Batch Reinforcement Learning

Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

Explainable Reinforcement Learning Through a Causal Lens

Double/Debiased/Neyman Machine Learning of Treatment Effects

Modeling User Exposure in Recommendation

Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics

Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations

Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging

A Theory of Regularized Markov Decision Processes

Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records

Deep Air Quality Forecasting Using Hybrid Deep Learning Framework

Quantization Networks

An Empirical Model of Large-Batch Training

Optimal Best Arm Identification with Fixed Confidence

Active Diffusion-Based Inference for Ill-Posed Inverse Problems under Incomplete Priors

Adversarial Training and Robustness for Multiple Perturbations

Understanding Measures of Uncertainty for Adversarial Example Detection

The Benefit of Multitask Representation Learning

ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks

TRACE-CRC: Trajectory-Adaptive Conformal Risk Control for Multi-Step Channel State Information Prediction

GANSynth: Adversarial Neural Audio Synthesis

Learning graphs from data: A signal representation perspective