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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5,041 to 5,100 of 6,786

AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
Chun-Chen Tu, Paishun Ting, Pin-Yu Chen +5
cs.CVcs.CRstat.MLarXiv:1805.11770v52018
PettingZoo: Gym for Multi-Agent Reinforcement Learning
J. K. Terry, Benjamin Black, Nathaniel Grammel +10
cs.LGcs.MAstat.MLarXiv:2009.14471v72020
Explainable Deep Learning: A Field Guide for the Uninitiated
Gabrielle Ras, Ning Xie, Marcel van Gerven +1
cs.LGcs.AIstat.MLarXiv:2004.14545v22020
Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff
Yochai Blau, Tomer Michaeli
cs.LGcs.CVcs.ITarXiv:1901.07821v42019
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes
Rachel Ward, Xiaoxia Wu, Leon Bottou
stat.MLcs.LGarXiv:1806.01811v82018
Single-Channel Multi-Speaker Separation using Deep Clustering
Yusuf Isik, Jonathan Le Roux, Zhuo Chen +2
cs.LGcs.SDstat.MLarXiv:1607.02173v12016
Residual Flows for Invertible Generative Modeling
Ricky T. Q. Chen, Jens Behrmann, David Duvenaud +1
stat.MLcs.LGarXiv:1906.02735v62019
Large scale distributed neural network training through online distillation
Rohan Anil, Gabriel Pereyra, Alexandre Passos +3
cs.LGcs.AIstat.MLarXiv:1804.03235v22018
Causal Confusion in Imitation Learning
Pim de Haan, Dinesh Jayaraman, Sergey Levine
cs.LGstat.MLarXiv:1905.11979v22019
On the Global Linear Convergence of Frank-Wolfe Optimization Variants
Simon Lacoste-Julien, Martin Jaggi
math.OCcs.LGstat.MLarXiv:1511.05932v12015
Which Metrics Save the Most Human Annotation? Prediction-Powered Evaluation and Meta-Evaluation
Mingqi Gao, Anthony Sicilia, Weiyan Shi
cs.CLstat.MLarXiv:2608.26638v12026
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
Jingfeng Zhang, Xilie Xu, Bo Han +4
cs.LGstat.MLarXiv:2002.11242v22020
lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits
Kevin Jamieson, Matthew Malloy, Robert Nowak +1
stat.MLcs.LGarXiv:1312.7308v12013
EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction
Youru Li, Zhenfeng Zhu, Deqiang Kong +2
cs.LGcs.NEstat.MLarXiv:1811.03760v12018
Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective
Guhao Feng, Bohang Zhang, Yuntian Gu +3
cs.LGcs.CCcs.CLarXiv:2305.15408v52023
Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions
K. T. Schütt, M. Gastegger, A. Tkatchenko +2
physics.chem-phstat.MLarXiv:1906.10033v12019
Analyzing and Improving the Training Dynamics of Diffusion Models
Tero Karras, Miika Aittala, Jaakko Lehtinen +3
cs.CVcs.AIcs.LGarXiv:2312.02696v22023
DALEX: explainers for complex predictive models
Przemyslaw Biecek
stat.MLcs.AIcs.LGarXiv:1806.08915v22018
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
cs.LGcs.DCmath.OCarXiv:1905.13727v32019
Fairness in Recommendation Ranking through Pairwise Comparisons
Alex Beutel, Jilin Chen, Tulsee Doshi +8
cs.CYcs.AIcs.IRarXiv:1903.00780v12019
Learning Gender-Neutral Word Embeddings
Jieyu Zhao, Yichao Zhou, Zeyu Li +2
cs.CLcs.LGstat.MLarXiv:1809.01496v12018
Diachronic Embedding for Temporal Knowledge Graph Completion
Rishab Goel, Seyed Mehran Kazemi, Marcus Brubaker +1
cs.LGcs.AIstat.MLarXiv:1907.03143v12019
Algorithm Runtime Prediction: Methods & Evaluation
Frank Hutter, Lin Xu, Holger H. Hoos +1
cs.AIcs.LGcs.PFarXiv:1211.0906v22012
Hadamard Flattening and Gaussian Pooling Sketch for Least Squares with Coordinate-wise Guarantee
Zhao Song, Lichen Zhang
cs.DScs.LGstat.MLarXiv:2608.26552v12026
A Continuous Time Framework for Discrete Denoising Models
Andrew Campbell, Joe Benton, Valentin De Bortoli +3
stat.MLcs.LGarXiv:2205.14987v22022
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations
Debraj Basu, Deepesh Data, Can Karakus +1
stat.MLcs.DCcs.LGarXiv:1906.02367v22019
Dataset Augmentation in Feature Space
Terrance DeVries, Graham W. Taylor
stat.MLcs.LGarXiv:1702.05538v12017
A Transformer-based Approach for Source Code Summarization
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray +1
cs.SEcs.AIcs.LGarXiv:2005.00653v12020
Transfer learning in hybrid classical-quantum neural networks
Andrea Mari, Thomas R. Bromley, Josh Izaac +2
quant-phcs.LGstat.MLarXiv:1912.08278v22019
Self-Supervised Exploration via Disagreement
Deepak Pathak, Dhiraj Gandhi, Abhinav Gupta
cs.LGcs.AIcs.CVarXiv:1906.04161v12019
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference
Alexandre Sablayrolles, Matthijs Douze, Yann Ollivier +2
stat.MLcs.CRcs.LGarXiv:1908.11229v12019
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable
Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal +2
cs.LGstat.MLarXiv:1610.09512v22016
The Diversity-Innovation Paradox in Science
Bas Hofstra, Vivek V. Kulkarni, Sebastian Munoz-Najar Galvez +3
cs.SIcs.CLstat.AParXiv:1909.02063v22019
Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs
Tristan Bepler, Andrew Morin, Julia Brasch +3
q-bio.QMcs.CVstat.MLarXiv:1803.08207v22018
Deep Reinforcement Learning for De-Novo Drug Design
Mariya Popova, Olexandr Isayev, Alexander Tropsha
cs.AIcs.LGstat.MLarXiv:1711.10907v22017
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
Sheng Wang, Siqi Sun, Zhen Li +2
q-bio.BMcs.LGq-bio.QMarXiv:1609.00680v62016
Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery
Kristina Preuer, Philipp Renz, Thomas Unterthiner +2
cs.LGq-bio.QMstat.MLarXiv:1803.09518v32018
Are Anchor Points Really Indispensable in Label-Noise Learning?
Xiaobo Xia, Tongliang Liu, Nannan Wang +4
cs.LGstat.MLarXiv:1906.00189v22019
Information Dropout: Learning Optimal Representations Through Noisy Computation
Alessandro Achille, Stefano Soatto
stat.MLcs.LGstat.COarXiv:1611.01353v32016
Adversarially Learned Anomaly Detection
Houssam Zenati, Manon Romain, Chuan Sheng Foo +2
cs.LGstat.MLarXiv:1812.02288v12018
TossingBot: Learning to Throw Arbitrary Objects with Residual Physics
Andy Zeng, Shuran Song, Johnny Lee +2
cs.ROcs.AIcs.CVarXiv:1903.11239v32019
Optimizing the Latent Space of Generative Networks
Piotr Bojanowski, Armand Joulin, David Lopez-Paz +1
stat.MLcs.CVcs.LGarXiv:1707.05776v22017
Algorithmic Principles For Multiclass Learning Are Hard To Come By: Limits of Regularization and Proper Learning
Julian Asilis, Shaddin Dughmi, Vatsal Sharan +3
cs.LGstat.MLarXiv:2608.26516v12026
Efficient Formal Safety Analysis of Neural Networks
Shiqi Wang, Kexin Pei, Justin Whitehouse +2
cs.LGcs.AIcs.LOarXiv:1809.08098v32018
Variational Quantum Circuits for Deep Reinforcement Learning
Samuel Yen-Chi Chen, Chao-Han Huck Yang, Jun Qi +3
cs.LGcs.AIquant-pharXiv:1907.00397v32019
Semidefinite relaxations for certifying robustness to adversarial examples
Aditi Raghunathan, Jacob Steinhardt, Percy Liang
cs.LGcs.CRstat.MLarXiv:1811.01057v12018
Explicit Bounds on the Entropy of Piecewise Hölder Graphon Models
Connor Loehde-Woolard, François G. Meyer
math.PRcs.SIstat.MLarXiv:2608.26501v12026
A Sufficient Condition for Convergences of Adam and RMSProp
Fangyu Zou, Li Shen, Zequn Jie +2
cs.LGcs.CVmath.NAarXiv:1811.09358v32018
Simple diffusion: End-to-end diffusion for high resolution images
Emiel Hoogeboom, Jonathan Heek, Tim Salimans
cs.CVcs.LGstat.MLarXiv:2301.11093v22023
Reducing Overfitting in Deep Networks by Decorrelating Representations
Michael Cogswell, Faruk Ahmed, Ross Girshick +2
cs.LGstat.MLarXiv:1511.06068v42015
Unsupervised Discovery of Interpretable Directions in the GAN Latent Space
Andrey Voynov, Artem Babenko
cs.LGcs.CVstat.MLarXiv:2002.03754v32020
Non-stationary Stochastic Optimization
O. Besbes, Y. Gur, A. Zeevi
math.PRcs.LGstat.MLarXiv:1307.5449v22013
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
Pengfei Chen, Benben Liao, Guangyong Chen +1
cs.LGstat.MLarXiv:1905.05040v12019
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification
Rohit Tripathy, Ilias Bilionis
physics.comp-phcs.LGstat.MLarXiv:1802.00850v12018
Using satellite imagery to understand and promote sustainable development
Marshall Burke, Anne Driscoll, David B. Lobell +1
cs.CYcs.CVcs.LGarXiv:2010.06988v12020
To tune or not to tune the number of trees in random forest?
Philipp Probst, Anne-Laure Boulesteix
stat.MLcs.LGarXiv:1705.05654v12017
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
David Balduzzi, Marcus Frean, Lennox Leary +3
cs.NEcs.LGstat.MLarXiv:1702.08591v22017
Under-determined reverberant audio source separation using a full-rank spatial covariance model
Ngoc Duong, Emmanuel Vincent, Remi Gribonval
stat.MLarXiv:0912.0171v22009
Automatic Posterior Transformation for Likelihood-Free Inference
David S. Greenberg, Marcel Nonnenmacher, Jakob H. Macke
cs.LGstat.MLarXiv:1905.07488v12019
Differentially Private Learning with Adaptive Clipping
Galen Andrew, Om Thakkar, H. Brendan McMahan +1
cs.LGstat.MLarXiv:1905.03871v52019

Machine Learning (stat)

AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks

PettingZoo: Gym for Multi-Agent Reinforcement Learning

Explainable Deep Learning: A Field Guide for the Uninitiated

Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff

AdaGrad stepsizes: Sharp convergence over nonconvex landscapes

Single-Channel Multi-Speaker Separation using Deep Clustering

Residual Flows for Invertible Generative Modeling

Large scale distributed neural network training through online distillation

Causal Confusion in Imitation Learning

On the Global Linear Convergence of Frank-Wolfe Optimization Variants

Which Metrics Save the Most Human Annotation? Prediction-Powered Evaluation and Meta-Evaluation

Attacks Which Do Not Kill Training Make Adversarial Learning Stronger

lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits

EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction

Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective

Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions

Analyzing and Improving the Training Dynamics of Diffusion Models

DALEX: explainers for complex predictive models

PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization

Fairness in Recommendation Ranking through Pairwise Comparisons

Learning Gender-Neutral Word Embeddings

Diachronic Embedding for Temporal Knowledge Graph Completion

Algorithm Runtime Prediction: Methods & Evaluation

Hadamard Flattening and Gaussian Pooling Sketch for Least Squares with Coordinate-wise Guarantee

A Continuous Time Framework for Discrete Denoising Models

Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations

Dataset Augmentation in Feature Space

A Transformer-based Approach for Source Code Summarization

Transfer learning in hybrid classical-quantum neural networks

Self-Supervised Exploration via Disagreement

White-box vs Black-box: Bayes Optimal Strategies for Membership Inference

Contextual Decision Processes with Low Bellman Rank are PAC-Learnable

The Diversity-Innovation Paradox in Science

Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs

Deep Reinforcement Learning for De-Novo Drug Design

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery

Are Anchor Points Really Indispensable in Label-Noise Learning?

Information Dropout: Learning Optimal Representations Through Noisy Computation

Adversarially Learned Anomaly Detection

TossingBot: Learning to Throw Arbitrary Objects with Residual Physics

Optimizing the Latent Space of Generative Networks

Algorithmic Principles For Multiclass Learning Are Hard To Come By: Limits of Regularization and Proper Learning

Efficient Formal Safety Analysis of Neural Networks

Variational Quantum Circuits for Deep Reinforcement Learning

Semidefinite relaxations for certifying robustness to adversarial examples

Explicit Bounds on the Entropy of Piecewise Hölder Graphon Models

A Sufficient Condition for Convergences of Adam and RMSProp

Simple diffusion: End-to-end diffusion for high resolution images

Reducing Overfitting in Deep Networks by Decorrelating Representations

Unsupervised Discovery of Interpretable Directions in the GAN Latent Space

Non-stationary Stochastic Optimization

Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels

Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification

Using satellite imagery to understand and promote sustainable development

To tune or not to tune the number of trees in random forest?

The Shattered Gradients Problem: If resnets are the answer, then what is the question?

Under-determined reverberant audio source separation using a full-rank spatial covariance model

Automatic Posterior Transformation for Likelihood-Free Inference

Differentially Private Learning with Adaptive Clipping