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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5,401 to 5,460 of 6,790

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
Marius Lindauer, Katharina Eggensperger, Matthias Feurer +6
cs.LGstat.MLarXiv:2109.09831v22021
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization
Yingfan Wang, Haiyang Huang, Cynthia Rudin +1
cs.LGstat.MLarXiv:2012.04456v22020
Attentive Neural Processes
Hyunjik Kim, Andriy Mnih, Jonathan Schwarz +5
cs.LGstat.MLarXiv:1901.05761v22019
Mapping the stereotyped behaviour of freely-moving fruit flies
Gordon J. Berman, Daniel M. Choi, William Bialek +1
q-bio.QMcs.CVphysics.bio-pharXiv:1310.4249v22013
Distributed Distributional Deterministic Policy Gradients
Gabriel Barth-Maron, Matthew W. Hoffman, David Budden +6
cs.LGcs.AIstat.MLarXiv:1804.08617v12018
Granger Causality: A Review and Recent Advances
Ali Shojaie, Emily B. Fox
stat.MEcs.LGstat.MLarXiv:2105.02675v22021
Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution
Thomas Elsken, Jan Hendrik Metzen, Frank Hutter
stat.MLcs.LGarXiv:1804.09081v42018
Toward Machine Learning with the Unit as a Primitive: Learning from Unit-Linked Events
Heyang Gong
cs.LGcs.AIstat.MLarXiv:2608.25118v12026
Multipole Graph Neural Operator for Parametric Partial Differential Equations
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli +4
cs.LGmath.NAstat.MLarXiv:2006.09535v22020
Quantum Natural Gradient
James Stokes, Josh Izaac, Nathan Killoran +1
quant-phcs.LGstat.MLarXiv:1909.02108v32019
Predictive Business Process Monitoring with LSTM Neural Networks
Niek Tax, Ilya Verenich, Marcello La Rosa +1
stat.APcs.DBcs.LGarXiv:1612.02130v22016
Bayesian Model-Agnostic Meta-Learning
Taesup Kim, Jaesik Yoon, Ousmane Dia +3
cs.LGstat.MLarXiv:1806.03836v42018
Three Factors Influencing Minima in SGD
Stanisław Jastrzębski, Zachary Kenton, Devansh Arpit +4
cs.LGcs.AIcs.CVarXiv:1711.04623v32017
Short-term Load Forecasting with Deep Residual Networks
Kunjin Chen, Kunlong Chen, Qin Wang +3
stat.MLcs.LGstat.AParXiv:1805.11956v12018
Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection
Seijoon Kim, Seongsik Park, Byunggook Na +1
cs.CVcs.LGstat.MLarXiv:1903.06530v22019
TarMAC: Targeted Multi-Agent Communication
Abhishek Das, Théophile Gervet, Joshua Romoff +4
cs.LGcs.AIcs.MAarXiv:1810.11187v22018
GRAPE: Gradient Refinement and Progress-Aware Exploitation for Query-Efficient High-Dimensional Bayesian Optimization
Richard Cornelius Suwandi, Feng Yin
cs.LGcs.AIstat.MLarXiv:2608.25116v12026
cpSGD: Communication-efficient and differentially-private distributed SGD
Naman Agarwal, Ananda Theertha Suresh, Felix Yu +2
stat.MLcs.CRcs.LGarXiv:1805.10559v12018
Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro
Du Phan, Neeraj Pradhan, Martin Jankowiak
stat.MLcs.AIcs.LGarXiv:1912.11554v12019
Non-convex Optimization for Machine Learning
Prateek Jain, Purushottam Kar
stat.MLcs.LGmath.OCarXiv:1712.07897v12017
Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging
Luke Oakden-Rayner, Jared Dunnmon, Gustavo Carneiro +1
cs.LGstat.MLarXiv:1909.12475v22019
Towards a Definition of Disentangled Representations
Irina Higgins, David Amos, David Pfau +4
cs.LGstat.MLarXiv:1812.02230v12018
(Mis)Understanding Benign Overfitting in Equity Return Prediction
Hui Guo, Jiawei Huang, Runze Li +1
stat.MLcs.LGstat.AParXiv:2608.23761v12026
What Regularized Auto-Encoders Learn from the Data Generating Distribution
Guillaume Alain, Yoshua Bengio
cs.LGstat.MLarXiv:1211.4246v52012
Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows
Nils Thuerey, Konstantin Weissenow, Lukas Prantl +1
cs.LGphysics.flu-dynstat.MLarXiv:1810.08217v32018
Clustering Algorithms: A Comparative Approach
Mayra Z. Rodriguez, Cesar H. Comin, Dalcimar Casanova +4
cs.LGstat.MLarXiv:1612.08388v12016
Understanding and Improving Layer Normalization
Jingjing Xu, Xu Sun, Zhiyuan Zhang +2
cs.LGcs.CLstat.MLarXiv:1911.07013v12019
Threats to Federated Learning: A Survey
Lingjuan Lyu, Han Yu, Qiang Yang
cs.CRcs.LGstat.MLarXiv:2003.02133v12020
Optimal approximation of piecewise smooth functions using deep ReLU neural networks
Philipp Petersen, Felix Voigtlaender
math.FAcs.LGstat.MLarXiv:1709.05289v42017
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
Matthias Hein, Maksym Andriushchenko
cs.LGcs.AIcs.CVarXiv:1705.08475v22017
NVExplain: Explaining Time Series Forecasting with Latent Trajectory Analysis and Structure-Preserving Surrogates
Muyan Anna Li, Manikandan Ravikiran, Aditi Gautam
cs.LGcs.AIstat.MLarXiv:2608.25080v12026
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges
Christoph Molnar, Giuseppe Casalicchio, Bernd Bischl
stat.MLcs.LGarXiv:2010.09337v12020
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks
Federico Monti, Michael M. Bronstein, Xavier Bresson
cs.LGcs.IRmath.NAarXiv:1704.06803v12017
Quantum machine learning: a classical perspective
Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo +4
quant-phcs.LGstat.MLarXiv:1707.08561v32017
Tensor2Tensor for Neural Machine Translation
Ashish Vaswani, Samy Bengio, Eugene Brevdo +10
cs.LGcs.CLstat.MLarXiv:1803.07416v12018
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting
Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou +1
cs.LGcs.SIstat.MLarXiv:2006.09252v32020
A Closer Look at Invalid Action Masking in Policy Gradient Algorithms
Shengyi Huang, Santiago Ontañón
cs.LGcs.AIstat.MLarXiv:2006.14171v32020
Representing MAX functions using two-hidden-layer ReLU networks
Zhimao Wang, Amitabh Basu
cs.LGmath.OCstat.MLarXiv:2608.25221v12026
Fairness in Machine Learning
Luca Oneto, Silvia Chiappa
cs.LGcs.CYstat.MLarXiv:2012.15816v12020
Convolutional Networks with Dense Connectivity
Gao Huang, Zhuang Liu, Geoff Pleiss +2
cs.LGcs.CVstat.MLarXiv:2001.02394v12020
Unifying distillation and privileged information
David Lopez-Paz, Léon Bottou, Bernhard Schölkopf +1
stat.MLcs.LGarXiv:1511.03643v32015
Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks
Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion
cs.CRcs.AIcs.LGarXiv:2404.02151v42024
Censoring Representations with an Adversary
Harrison Edwards, Amos Storkey
cs.LGcs.AIstat.MLarXiv:1511.05897v32015
Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate
Xiao Ma, Liqin Zhao, Guan Huang +4
stat.MLcs.IRcs.LGarXiv:1804.07931v22018
Machine Learning with Membership Privacy using Adversarial Regularization
Milad Nasr, Reza Shokri, Amir Houmansadr
stat.MLcs.CRcs.LGarXiv:1807.05852v12018
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
Kaiyu Yang, Aidan M. Swope, Alex Gu +6
cs.LGcs.AIcs.LOarXiv:2306.15626v22023
Momentum-Based Variance Reduction in Non-Convex SGD
Ashok Cutkosky, Francesco Orabona
cs.LGmath.OCstat.MLarXiv:1905.10018v32019
Beyond Optimal Rates in Stochastic Optimization: Trajectory-Adaptive Stopping Rules
Liviu Aolaritei, Lucas Lévy, Francis Bach +1
cs.LGmath.OCmath.STarXiv:2608.25551v12026
The Convergence of Sparsified Gradient Methods
Dan Alistarh, Torsten Hoefler, Mikael Johansson +3
cs.LGcs.DCstat.MLarXiv:1809.10505v12018
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
Adam Roberts, Jesse Engel, Colin Raffel +2
cs.LGcs.SDeess.ASarXiv:1803.05428v52018
Temporal Link Prediction using Matrix and Tensor Factorizations
Daniel M. Dunlavy, Tamara G. Kolda, Evrim Acar
math.NAphysics.data-anstat.MLarXiv:1005.4006v22010
Deep Reinforcement Learning for Cyber Security
Thanh Thi Nguyen, Vijay Janapa Reddi
cs.CRcs.AIcs.LGarXiv:1906.05799v42019
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Pengyu Cheng, Weituo Hao, Shuyang Dai +3
cs.LGstat.MLarXiv:2006.12013v62020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Chence Shi, Minkai Xu, Zhaocheng Zhu +3
cs.LGstat.MLarXiv:2001.09382v22020
Learning Factorized Multimodal Representations
Yao-Hung Hubert Tsai, Paul Pu Liang, Amir Zadeh +2
cs.LGcs.CLcs.CVarXiv:1806.06176v32018
Structure Discovery in Nonparametric Regression through Compositional Kernel Search
David Duvenaud, James Robert Lloyd, Roger Grosse +2
stat.MLcs.LGstat.MEarXiv:1302.4922v42013
A Semantic Loss Function for Deep Learning with Symbolic Knowledge
Jingyi Xu, Zilu Zhang, Tal Friedman +2
cs.AIcs.LGcs.LOarXiv:1711.11157v22017
Deep neural network solution of the electronic Schrödinger equation
Jan Hermann, Zeno Schätzle, Frank Noé
physics.comp-phcs.LGphysics.chem-pharXiv:1909.08423v52019
Asynchronous Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian, Wei Zhang, Ce Zhang +1
math.OCcs.LGstat.MLarXiv:1710.06952v32017
Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks
Davood Karimi, Septimiu E. Salcudean
eess.IVcs.LGstat.MLarXiv:1904.10030v12019

Machine Learning (stat)

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization

Attentive Neural Processes

Mapping the stereotyped behaviour of freely-moving fruit flies

Distributed Distributional Deterministic Policy Gradients

Granger Causality: A Review and Recent Advances

Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution

Toward Machine Learning with the Unit as a Primitive: Learning from Unit-Linked Events

Multipole Graph Neural Operator for Parametric Partial Differential Equations

Quantum Natural Gradient

Predictive Business Process Monitoring with LSTM Neural Networks

Bayesian Model-Agnostic Meta-Learning

Three Factors Influencing Minima in SGD

Short-term Load Forecasting with Deep Residual Networks

Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection

TarMAC: Targeted Multi-Agent Communication

GRAPE: Gradient Refinement and Progress-Aware Exploitation for Query-Efficient High-Dimensional Bayesian Optimization

cpSGD: Communication-efficient and differentially-private distributed SGD

Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro

Non-convex Optimization for Machine Learning

Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging

Towards a Definition of Disentangled Representations

(Mis)Understanding Benign Overfitting in Equity Return Prediction

What Regularized Auto-Encoders Learn from the Data Generating Distribution

Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows

Clustering Algorithms: A Comparative Approach

Understanding and Improving Layer Normalization

Threats to Federated Learning: A Survey

Optimal approximation of piecewise smooth functions using deep ReLU neural networks

Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation

NVExplain: Explaining Time Series Forecasting with Latent Trajectory Analysis and Structure-Preserving Surrogates

Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges

Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks

Quantum machine learning: a classical perspective

Tensor2Tensor for Neural Machine Translation

Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting

A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

Representing MAX functions using two-hidden-layer ReLU networks

Fairness in Machine Learning

Convolutional Networks with Dense Connectivity

Unifying distillation and privileged information

Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks

Censoring Representations with an Adversary

Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate

Machine Learning with Membership Privacy using Adversarial Regularization

LeanDojo: Theorem Proving with Retrieval-Augmented Language Models

Momentum-Based Variance Reduction in Non-Convex SGD

Beyond Optimal Rates in Stochastic Optimization: Trajectory-Adaptive Stopping Rules

The Convergence of Sparsified Gradient Methods

A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music

Temporal Link Prediction using Matrix and Tensor Factorizations

Deep Reinforcement Learning for Cyber Security

CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

Learning Factorized Multimodal Representations

Structure Discovery in Nonparametric Regression through Compositional Kernel Search

A Semantic Loss Function for Deep Learning with Symbolic Knowledge

Deep neural network solution of the electronic Schrödinger equation

Asynchronous Decentralized Parallel Stochastic Gradient Descent

Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks