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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661 to 720 of 6,785

Visual Causal Feature Learning
Krzysztof Chalupka, Pietro Perona, Frederick Eberhardt
stat.MLcs.AIcs.CVarXiv:1412.2309v22014
Methods of Hierarchical Clustering
Fionn Murtagh, Pedro Contreras
cs.IRcs.CVmath.STarXiv:1105.0121v12011
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
Yizhen Wang, Somesh Jha, Kamalika Chaudhuri
stat.MLcs.CRcs.LGarXiv:1706.03922v62017
Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance
Taylor Denouden, Rick Salay, Krzysztof Czarnecki +3
cs.LGstat.MLarXiv:1812.02765v12018
Augmenting Self-attention with Persistent Memory
Sainbayar Sukhbaatar, Edouard Grave, Guillaume Lample +2
cs.LGcs.CLstat.MLarXiv:1907.01470v12019
Random Utility Theory for Social Choice
Hossein Azari Soufiani, David C. Parkes, Lirong Xia
cs.MAcs.LGstat.MLarXiv:1211.2476v12012
The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies
Stephan Zheng, Alexander Trott, Sunil Srinivasa +4
econ.GNcs.LGstat.MLarXiv:2004.13332v12020
The Limitations of Adversarial Training and the Blind-Spot Attack
Huan Zhang, Hongge Chen, Zhao Song +3
stat.MLcs.CRcs.CVarXiv:1901.04684v12019
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks
Jingkun Gao, Xiaomin Song, Qingsong Wen +3
cs.LGeess.SPstat.AParXiv:2002.09545v22020
OmniFold: A Method to Simultaneously Unfold All Observables
Anders Andreassen, Patrick T. Komiske, Eric M. Metodiev +2
hep-phhep-exphysics.data-anarXiv:1911.09107v22019
An Analysis of the Convergence of Graph Laplacians
Daniel Ting, Ling Huang, Michael Jordan
stat.MLarXiv:1101.5435v12011
Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures
Luke Vilnis, Xiang Li, Shikhar Murty +1
stat.MLcs.LGarXiv:1805.06627v12018
What Fixed-Rollout pass@k Evaluations Can Identify
Pranav Singh, Prashant Singh
stat.MLcs.AIcs.LGarXiv:2609.09245v12026
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
Robert Peharz, Steven Lang, Antonio Vergari +6
cs.LGstat.MLarXiv:2004.06231v22020
Critical initialization destabilizes higher input derivatives in wide scalar-input networks
Prashant Singh, Pranav Singh
stat.MLcs.AIcs.LGarXiv:2609.09244v12026
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
Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees
Guiliang Liu, Oliver Schulte, Wang Zhu +1
cs.LGstat.MLarXiv:1807.05887v12018
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings
John D. Co-Reyes, YuXuan Liu, Abhishek Gupta +3
cs.LGcs.AIstat.MLarXiv:1806.02813v12018
Model-based Pricing for Machine Learning in a Data Marketplace
Lingjiao Chen, Paraschos Koutris, Arun Kumar
cs.DBcs.GTcs.LGarXiv:1805.11450v12018
How Important Is a Neuron?
Kedar Dhamdhere, Mukund Sundararajan, Qiqi Yan
cs.LGstat.MLarXiv:1805.12233v12018
Infinite attention: NNGP and NTK for deep attention networks
Jiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein +1
stat.MLcs.LGarXiv:2006.10540v12020
Yes, but Did It Work?: Evaluating Variational Inference
Yuling Yao, Aki Vehtari, Daniel Simpson +1
stat.MLstat.COarXiv:1802.02538v22018
The Directed Closure Process in Hybrid Social-Information Networks, with an Analysis of Link Formation on Twitter
Daniel M. Romero, Jon Kleinberg
stat.MLcs.CYphysics.soc-pharXiv:1003.2469v12010
Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network
Bai Jiang, Tung-yu Wu, Charles Zheng +1
stat.MEstat.COstat.MLarXiv:1510.02175v32015
Double/Debiased Machine Learning for Treatment and Causal Parameters
Victor Chernozhukov, Denis Chetverikov, Mert Demirer +4
stat.MLecon.EMarXiv:1608.00060v72016
Directed Graph Convolutional Network
Zekun Tong, Yuxuan Liang, Changsheng Sun +2
cs.LGstat.MLarXiv:2004.13970v12020
Active and passive learning of linear separators under log-concave distributions
Maria Florina Balcan, Philip M. Long
cs.LGmath.STstat.MLarXiv:1211.1082v32012
Live Face De-Identification in Video
Oran Gafni, Lior Wolf, Yaniv Taigman
cs.LGcs.CVcs.GRarXiv:1911.08348v12019
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search
Linnan Wang, Rodrigo Fonseca, Yuandong Tian
cs.LGcs.AIcs.ROarXiv:2007.00708v22020
On Contrastive Learning for Likelihood-free Inference
Conor Durkan, Iain Murray, George Papamakarios
stat.MLcs.LGarXiv:2002.03712v22020
A Tensor Approach to Learning Mixed Membership Community Models
Anima Anandkumar, Rong Ge, Daniel Hsu +1
cs.LGcs.SIstat.MLarXiv:1302.2684v42013
Omnigrok: Grokking Beyond Algorithmic Data
Ziming Liu, Eric J. Michaud, Max Tegmark
cs.LGcs.AIphysics.data-anarXiv:2210.01117v22022
Nonparametric variational inference
Samuel Gershman, Matt Hoffman, David Blei
cs.LGstat.MLarXiv:1206.4665v12012
Quasi-hyperbolic momentum and Adam for deep learning
Jerry Ma, Denis Yarats
cs.LGstat.MLarXiv:1810.06801v42018
Fair Mixup: Fairness via Interpolation
Ching-Yao Chuang, Youssef Mroueh
cs.LGcs.CYstat.MLarXiv:2103.06503v12021
A Survey on Large-scale Machine Learning
Meng Wang, Weijie Fu, Xiangnan He +2
cs.LGstat.MLarXiv:2008.03911v12020
Gaussian Processes for Nonlinear Signal Processing
Fernando Pérez-Cruz, Steven Van Vaerenbergh, Juan José Murillo-Fuentes +2
cs.LGcs.ITstat.MLarXiv:1303.2823v22013
Lipschitz constant estimation of Neural Networks via sparse polynomial optimization
Fabian Latorre, Paul Rolland, Volkan Cevher
cs.LGstat.MLarXiv:2004.08688v12020
A jamming transition from under- to over-parametrization affects loss landscape and generalization
Stefano Spigler, Mario Geiger, Stéphane d'Ascoli +3
cs.LGcond-mat.dis-nnstat.MLarXiv:1810.09665v52018
Kernel Risk-Sensitive Loss: Definition, Properties and Application to Robust Adaptive Filtering
Badong Chen, Lei Xing, Bin Xu +3
stat.MLarXiv:1608.00441v12016
Explaining the Success of Nearest Neighbor Methods in Prediction
George H. Chen, Devavrat Shah
cs.LGstat.MLarXiv:2502.15900v12025
Winning the Lottery with Continuous Sparsification
Pedro Savarese, Hugo Silva, Michael Maire
cs.LGstat.MLarXiv:1912.04427v42019
Abnormal Client Behavior Detection in Federated Learning
Suyi Li, Yong Cheng, Yang Liu +2
cs.LGstat.MLarXiv:1910.09933v22019
Adaptive pooling operators for weakly labeled sound event detection
Brian McFee, Justin Salamon, Juan Pablo Bello
cs.SDcs.LGeess.ASarXiv:1804.10070v22018
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure
Saeed Mahloujifar, Dimitrios I. Diochnos, Mohammad Mahmoody
cs.LGcs.CCcs.CRarXiv:1809.03063v22018
DFacTo: Distributed Factorization of Tensors
Joon Hee Choi, S. V. N. Vishwanathan
stat.MLarXiv:1406.4519v12014
GPU-Enabled Large-Scale Optimization Using Randomized Linear Algebra
Pratik Rathore, Zachary Frangella, Parth Nobel +2
cs.LGmath.OCstat.MLarXiv:2609.08136v12026
Robust and interpretable blind image denoising via bias-free convolutional neural networks
Sreyas Mohan, Zahra Kadkhodaie, Eero P. Simoncelli +1
eess.IVcs.CVcs.LGarXiv:1906.05478v32019
Deep splitting method for parabolic PDEs
Christian Beck, Sebastian Becker, Patrick Cheridito +2
math.NAcs.LGmath.PRarXiv:1907.03452v22019
Stable Prediction with Model Misspecification and Agnostic Distribution Shift
Kun Kuang, Ruoxuan Xiong, Peng Cui +2
cs.LGstat.MLarXiv:2001.11713v12020
Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks
Cem M. Deniz, Siyuan Xiang, Spencer Hallyburton +5
cs.CVcs.LGstat.MLarXiv:1704.06176v52017
Minimum Width for Universal Approximation
Sejun Park, Chulhee Yun, Jaeho Lee +1
cs.LGstat.MLarXiv:2006.08859v12020
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan +1
math.OCcs.LGstat.MLarXiv:1902.05679v22019
NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks
Ermao Cai, Da-Cheng Juan, Dimitrios Stamoulis +1
cs.LGcs.PFstat.MLarXiv:1710.05420v12017
Influence-Based Multi-Agent Exploration
Tonghan Wang, Jianhao Wang, Yi Wu +1
cs.LGcs.MAstat.MLarXiv:1910.05512v12019
HEAR: Holistic Evaluation of Audio Representations
Joseph Turian, Jordie Shier, Humair Raj Khan +20
cs.SDcs.AIcs.LGarXiv:2203.03022v32022
Differentially Private Diffusion Models
Tim Dockhorn, Tianshi Cao, Arash Vahdat +1
stat.MLcs.CRcs.LGarXiv:2210.09929v32022
Scalable Recommendation with Poisson Factorization
Prem Gopalan, Jake M. Hofman, David M. Blei
cs.IRcs.AIcs.LGarXiv:1311.1704v32013
Stochastic Frank-Wolfe Methods for Nonconvex Optimization
Sashank J. Reddi, Suvrit Sra, Barnabas Poczos +1
math.OCcs.LGstat.MLarXiv:1607.08254v22016
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
Gintare Karolina Dziugaite, Daniel M. Roy
stat.MLcs.LGarXiv:1712.09376v32017

Machine Learning (stat)

Visual Causal Feature Learning

Methods of Hierarchical Clustering

Analyzing the Robustness of Nearest Neighbors to Adversarial Examples

Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Augmenting Self-attention with Persistent Memory

Random Utility Theory for Social Choice

The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies

The Limitations of Adversarial Training and the Blind-Spot Attack

RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks

OmniFold: A Method to Simultaneously Unfold All Observables

An Analysis of the Convergence of Graph Laplacians

Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures

What Fixed-Rollout pass@k Evaluations Can Identify

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

Critical initialization destabilizes higher input derivatives in wide scalar-input networks

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

Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees

Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings

Model-based Pricing for Machine Learning in a Data Marketplace

How Important Is a Neuron?

Infinite attention: NNGP and NTK for deep attention networks

Yes, but Did It Work?: Evaluating Variational Inference

The Directed Closure Process in Hybrid Social-Information Networks, with an Analysis of Link Formation on Twitter

Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network

Double/Debiased Machine Learning for Treatment and Causal Parameters

Directed Graph Convolutional Network

Active and passive learning of linear separators under log-concave distributions

Live Face De-Identification in Video

Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search

On Contrastive Learning for Likelihood-free Inference

A Tensor Approach to Learning Mixed Membership Community Models

Omnigrok: Grokking Beyond Algorithmic Data

Nonparametric variational inference

Quasi-hyperbolic momentum and Adam for deep learning

Fair Mixup: Fairness via Interpolation

A Survey on Large-scale Machine Learning

Gaussian Processes for Nonlinear Signal Processing

Lipschitz constant estimation of Neural Networks via sparse polynomial optimization

A jamming transition from under- to over-parametrization affects loss landscape and generalization

Kernel Risk-Sensitive Loss: Definition, Properties and Application to Robust Adaptive Filtering

Explaining the Success of Nearest Neighbor Methods in Prediction

Winning the Lottery with Continuous Sparsification

Abnormal Client Behavior Detection in Federated Learning

Adaptive pooling operators for weakly labeled sound event detection

The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure

DFacTo: Distributed Factorization of Tensors

GPU-Enabled Large-Scale Optimization Using Randomized Linear Algebra

Robust and interpretable blind image denoising via bias-free convolutional neural networks

Deep splitting method for parabolic PDEs

Stable Prediction with Model Misspecification and Agnostic Distribution Shift

Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks

Minimum Width for Universal Approximation

ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization

NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks

Influence-Based Multi-Agent Exploration

HEAR: Holistic Evaluation of Audio Representations

Differentially Private Diffusion Models

Scalable Recommendation with Poisson Factorization

Stochastic Frank-Wolfe Methods for Nonconvex Optimization

Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors