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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3,481 to 3,540 of 6,785

Localizing Global Discrepancies: Marginal Contributions and Contextual Anomaly Detection
Tommaso dorigo
stat.MLcs.LGphysics.data-anarXiv:2608.28375v12026
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
Ari S. Morcos, Haonan Yu, Michela Paganini +1
stat.MLcs.LGcs.NEarXiv:1906.02773v22019
Adversarial Training Can Hurt Generalization
Aditi Raghunathan, Sang Michael Xie, Fanny Yang +2
cs.LGstat.MLarXiv:1906.06032v22019
Multiview Hessian Regularization for Image Annotation
Weifeng Liu, Dacheng Tao
cs.LGcs.CVstat.MLarXiv:1904.10100v12019
Application of Quantum Annealing to Training of Deep Neural Networks
Steven H. Adachi, Maxwell P. Henderson
quant-phcs.LGstat.MLarXiv:1510.06356v12015
I-FLOP: Fast Learning of Order and Parents from Interventional Data
Liuting Chen, Alex Markham
stat.MLcs.LGarXiv:2608.28245v12026
Stochastic seismic waveform inversion using generative adversarial networks as a geological prior
Lukas Mosser, Olivier Dubrule, Martin J. Blunt
physics.geo-phcs.CVstat.MLarXiv:1806.03720v12018
On Sampling Strategies for Neural Network-based Collaborative Filtering
Ting Chen, Yizhou Sun, Yue Shi +1
cs.LGcs.IRcs.SIarXiv:1706.07881v12017
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy
Aditi Raghunathan, Sang Michael Xie, Fanny Yang +2
cs.LGstat.MLarXiv:2002.10716v22020
Model-Based Reinforcement Learning via Meta-Policy Optimization
Ignasi Clavera, Jonas Rothfuss, John Schulman +3
cs.LGcs.AIstat.MLarXiv:1809.05214v12018
Exploring the Regularity of Sparse Structure in Convolutional Neural Networks
Huizi Mao, Song Han, Jeff Pool +4
cs.LGstat.MLarXiv:1705.08922v32017
Delving into adversarial attacks on deep policies
Jernej Kos, Dawn Song
stat.MLcs.LGarXiv:1705.06452v12017
Spectral Bias and Task-Model Alignment Explain Generalization in Kernel Regression and Infinitely Wide Neural Networks
Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan
stat.MLcond-mat.dis-nncs.LGarXiv:2006.13198v62020
Natasha 2: Faster Non-Convex Optimization Than SGD
Zeyuan Allen-Zhu
math.OCcs.DScs.LGarXiv:1708.08694v42017
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD
Jianyu Wang, Gauri Joshi
cs.LGcs.DCstat.MLarXiv:1810.08313v22018
Learning Model-Agnostic Counterfactual Explanations for Tabular Data
Martin Pawelczyk, Johannes Haug, Klaus Broelemann +1
cs.LGstat.MLarXiv:1910.09398v22019
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo
Yu-Xiang Wang, Stephen E. Fienberg, Alex Smola
stat.MLcs.LGarXiv:1502.07645v22015
Generalized Gibbs Ensemble Weighting for Forecast Combination
Prasen R. Nuthanakaluva, Nava K. Gaddam
cs.LGstat.MLarXiv:2608.28116v12026
Sylvester Normalizing Flows for Variational Inference
Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak +1
stat.MLcs.AIcs.LGarXiv:1803.05649v22018
Offline A/B testing for Recommender Systems
Alexandre Gilotte, Clément Calauzènes, Thomas Nedelec +2
stat.MLcs.LGarXiv:1801.07030v12018
Deep Neural Network Approximation Theory
Dennis Elbrächter, Dmytro Perekrestenko, Philipp Grohs +1
cs.LGcs.ITstat.MLarXiv:1901.02220v42019
Fisher-Rao Metric, Geometry, and Complexity of Neural Networks
Tengyuan Liang, Tomaso Poggio, Alexander Rakhlin +1
cs.LGcs.AIstat.MLarXiv:1711.01530v22017
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
Hao Cheng, Zhaowei Zhu, Xingyu Li +3
cs.LGstat.MLarXiv:2010.02347v22020
Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations
Aditya Golatkar, Alessandro Achille, Stefano Soatto
cs.LGcs.CVcs.ITarXiv:2003.02960v32020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
Silviu-Marian Udrescu, Andrew Tan, Jiahai Feng +3
cs.LGcs.AIcs.ITarXiv:2006.10782v22020
MedDialog: Two Large-scale Medical Dialogue Datasets
Xuehai He, Shu Chen, Zeqian Ju +10
cs.LGcs.AIcs.CLarXiv:2004.03329v22020
Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks
Santiago Pascual, Mirco Ravanelli, Joan Serrà +2
cs.LGcs.SDeess.ASarXiv:1904.03416v12019
One-Shot Generalization in Deep Generative Models
Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka +2
stat.MLcs.AIcs.LGarXiv:1603.05106v22016
A path algorithm for the Fused Lasso Signal Approximator
Holger Hoefling
stat.COstat.MLarXiv:0910.0526v12009
Venture: a higher-order probabilistic programming platform with programmable inference
Vikash Mansinghka, Daniel Selsam, Yura Perov
cs.AIcs.PLstat.COarXiv:1404.0099v12014
On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset
Abien Fred Agarap
cs.LGstat.MLarXiv:1711.07831v42017
Neural Tangents: Fast and Easy Infinite Neural Networks in Python
Roman Novak, Lechao Xiao, Jiri Hron +4
stat.MLcs.LGarXiv:1912.02803v12019
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge
Laura Rieger, Chandan Singh, W. James Murdoch +1
cs.LGcs.CVstat.MLarXiv:1909.13584v42019
An Open Source AutoML Benchmark
Pieter Gijsbers, Erin LeDell, Janek Thomas +3
cs.LGstat.MLarXiv:1907.00909v12019
A continual learning survey: Defying forgetting in classification tasks
Matthias De Lange, Rahaf Aljundi, Marc Masana +5
cs.CVstat.MLarXiv:1909.08383v32019
Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation
Chao Chen, Zhihong Chen, Boyuan Jiang +1
cs.LGcs.CVstat.MLarXiv:1808.09347v22018
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon S. Du, Chi Jin, Jason D. Lee +3
math.OCcs.LGstat.MLarXiv:1705.10412v22017
Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning
Supasorn Suwajanakorn, Noah Snavely, Jonathan Tompson +1
cs.CVcs.LGstat.MLarXiv:1807.03146v22018
Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement
Samuel Daulton, Maximilian Balandat, Eytan Bakshy
cs.LGcs.AIstat.MLarXiv:2105.08195v22021
Similarity encoding for learning with dirty categorical variables
Patricio Cerda, Gaël Varoquaux, Balázs Kégl
cs.LGcs.AIstat.MLarXiv:1806.00979v12018
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation
Rudra P K Poudel, Pablo Lamata, Giovanni Montana
stat.MLcs.CVcs.LGarXiv:1608.03974v12016
Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability
Benjamin A. Toms, Elizabeth A. Barnes, Imme Ebert-Uphoff
physics.ao-phcs.AIphysics.data-anarXiv:1912.01752v22019
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
Ben Athiwaratkun, Marc Finzi, Pavel Izmailov +1
cs.LGcs.AIcs.CVarXiv:1806.05594v32018
Consistency and fluctuations for stochastic gradient Langevin dynamics
Yee Whye Teh, Alexandre Thiéry, Sebastian Vollmer
stat.MLarXiv:1409.0578v22014
An Iterative BP-CNN Architecture for Channel Decoding
Fei Liang, Cong Shen, Feng Wu
stat.MLcs.ITarXiv:1707.05697v12017
Emergence of grid-like representations by training recurrent neural networks to perform spatial localization
Christopher J. Cueva, Xue-Xin Wei
q-bio.NCcs.AIcs.NEarXiv:1803.07770v12018
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
Gilles Blanchard, Marek Flaska, Gregory Handy +2
stat.MLcs.LGarXiv:1303.1208v32013
Exact Gaussian Processes on a Million Data Points
Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner +3
cs.LGcs.DCstat.MLarXiv:1903.08114v22019
Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings
Rie Johnson, Tong Zhang
stat.MLcs.CLcs.LGarXiv:1602.02373v22016
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
Yilun Du, Conor Durkan, Robin Strudel +6
cs.LGcs.AIcs.CVarXiv:2302.11552v62023
Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables
Yichi Zhang, Daniel Apley, Wei Chen
stat.MLcond-mat.mtrl-scics.LGarXiv:1910.01688v12019
Smooth Neighbors on Teacher Graphs for Semi-supervised Learning
Yucen Luo, Jun Zhu, Mengxi Li +2
cs.LGcs.NEstat.MLarXiv:1711.00258v22017
Optimal Transport for Network Comparison: A Review with Machine Learning Applications
James Hyun, François G. Meyer
stat.MLcs.LGcs.SIarXiv:2608.27500v12026
Lossy Image Compression with Conditional Diffusion Models
Ruihan Yang, Stephan Mandt
eess.IVcs.CVcs.LGarXiv:2209.06950v82022
XRAI: Better Attributions Through Regions
Andrei Kapishnikov, Tolga Bolukbasi, Fernanda Viégas +1
cs.CVstat.MLarXiv:1906.02825v22019
A Review of Stochastic Block Models and Extensions for Graph Clustering
Clement Lee, Darren J Wilkinson
stat.MLcs.LGarXiv:1903.00114v22019
Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran
Mostafa Emadi, Ruhollah Taghizadeh-Mehrjardi, Ali Cherati +3
cs.LGstat.MLarXiv:2007.12475v12020
Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges
Lei Lei, Yue Tan, Kan Zheng +4
cs.LGstat.MLarXiv:1907.09059v32019
Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis
Jingyuan Wang, Ze Wang, Jianfeng Li +1
cs.LGeess.SPstat.MLarXiv:1806.08946v12018
Kaggle forecasting competitions: An overlooked learning opportunity
Casper Solheim Bojer, Jens Peder Meldgaard
stat.MLcs.LGstat.AParXiv:2009.07701v12020

Machine Learning (stat)

Localizing Global Discrepancies: Marginal Contributions and Contextual Anomaly Detection

One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers

Adversarial Training Can Hurt Generalization

Multiview Hessian Regularization for Image Annotation

Application of Quantum Annealing to Training of Deep Neural Networks

I-FLOP: Fast Learning of Order and Parents from Interventional Data

Stochastic seismic waveform inversion using generative adversarial networks as a geological prior

On Sampling Strategies for Neural Network-based Collaborative Filtering

Understanding and Mitigating the Tradeoff Between Robustness and Accuracy

Model-Based Reinforcement Learning via Meta-Policy Optimization

Exploring the Regularity of Sparse Structure in Convolutional Neural Networks

Delving into adversarial attacks on deep policies

Spectral Bias and Task-Model Alignment Explain Generalization in Kernel Regression and Infinitely Wide Neural Networks

Natasha 2: Faster Non-Convex Optimization Than SGD

Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD

Learning Model-Agnostic Counterfactual Explanations for Tabular Data

Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo

Generalized Gibbs Ensemble Weighting for Forecast Combination

Sylvester Normalizing Flows for Variational Inference

Offline A/B testing for Recommender Systems

Deep Neural Network Approximation Theory

Fisher-Rao Metric, Geometry, and Complexity of Neural Networks

Learning with Instance-Dependent Label Noise: A Sample Sieve Approach

Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations

AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity

MedDialog: Two Large-scale Medical Dialogue Datasets

Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks

One-Shot Generalization in Deep Generative Models

A path algorithm for the Fused Lasso Signal Approximator

Venture: a higher-order probabilistic programming platform with programmable inference

On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

Neural Tangents: Fast and Easy Infinite Neural Networks in Python

Interpretations are useful: penalizing explanations to align neural networks with prior knowledge

An Open Source AutoML Benchmark

A continual learning survey: Defying forgetting in classification tasks

Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation

Gradient Descent Can Take Exponential Time to Escape Saddle Points

Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning

Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement

Similarity encoding for learning with dirty categorical variables

Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation

Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability

There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average

Consistency and fluctuations for stochastic gradient Langevin dynamics

An Iterative BP-CNN Architecture for Channel Decoding

Emergence of grid-like representations by training recurrent neural networks to perform spatial localization

Classification with Asymmetric Label Noise: Consistency and Maximal Denoising

Exact Gaussian Processes on a Million Data Points

Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings

Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC

Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables

Smooth Neighbors on Teacher Graphs for Semi-supervised Learning

Optimal Transport for Network Comparison: A Review with Machine Learning Applications

Lossy Image Compression with Conditional Diffusion Models

XRAI: Better Attributions Through Regions

A Review of Stochastic Block Models and Extensions for Graph Clustering

Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran

Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges

Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis

Kaggle forecasting competitions: An overlooked learning opportunity