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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2,821 to 2,880 of 6,792

Functional Regularisation for Continual Learning with Gaussian Processes
Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews +2
stat.MLcs.LGarXiv:1901.11356v42019
Recurrent Quantum Neural Networks
Johannes Bausch
cs.LGquant-phstat.MLarXiv:2006.14619v12020
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness
Pu Zhao, Pin-Yu Chen, Payel Das +2
cs.LGcs.CVstat.MLarXiv:2005.00060v22020
Convolutional Dictionary Learning: A Comparative Review and New Algorithms
Cristina Garcia-Cardona, Brendt Wohlberg
cs.LGeess.IVstat.MLarXiv:1709.02893v52017
DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks
Aryan Mobiny, Hien V. Nguyen, Supratik Moulik +2
cs.LGcs.AIcs.CVarXiv:1906.04569v12019
Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification
Xiaoyu Cao, Neil Zhenqiang Gong
cs.CRcs.LGstat.MLarXiv:1709.05583v42017
Gradient Descent Converges to Minimizers
Jason D. Lee, Max Simchowitz, Michael I. Jordan +1
stat.MLcs.LGmath.OCarXiv:1602.04915v22016
Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion
Longhao Yuan, Chao Li, Danilo Mandic +2
cs.LGcs.CVstat.MLarXiv:1809.02288v22018
Efficiently learning Ising models on arbitrary graphs
Guy Bresler
cs.LGcs.ITstat.MLarXiv:1411.6156v22014
Parsimonious module inference in large networks
Tiago P. Peixoto
physics.data-anphysics.soc-phstat.MLarXiv:1212.4794v42012
ABC random forests for Bayesian parameter inference
Louis Raynal, Jean-Michel Marin, Pierre Pudlo +3
stat.MEstat.COstat.MLarXiv:1605.05537v52016
High-dimensional learning of linear causal networks via inverse covariance estimation
Po-Ling Loh, Peter Bühlmann
stat.MLmath.STarXiv:1311.3492v12013
Explaining Classifiers with Causal Concept Effect (CaCE)
Yash Goyal, Amir Feder, Uri Shalit +1
cs.LGcs.CVstat.MLarXiv:1907.07165v22019
Datamodels: Predicting Predictions from Training Data
Andrew Ilyas, Sung Min Park, Logan Engstrom +2
stat.MLcs.CVcs.LGarXiv:2202.00622v12022
NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size
Xuanyi Dong, Lu Liu, Katarzyna Musial +1
cs.LGstat.MLarXiv:2009.00437v62020
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Tom Zahavy, Matan Haroush, Nadav Merlis +2
cs.LGstat.MLarXiv:1809.02121v32018
HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction
Bhaskarjit Sarmah, Benika Hall, Rohan Rao +3
cs.CLcs.LGq-fin.STarXiv:2408.04948v12024
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
Jian Guo, He He, Tong He +13
cs.LGcs.CLcs.CVarXiv:1907.04433v22019
Exact Global MCMC with Denoising Diffusion
Mitch Hill
stat.MLcs.LGarXiv:2609.00279v12026
Visualizing the Feature Importance for Black Box Models
Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl
stat.MLcs.AIcs.LGarXiv:1804.06620v32018
Cost-Sensitive Support Vector Machines
Hamed Masnadi-Shirazi, Nuno Vasconcelos, Arya Iranmehr
cs.LGstat.MLarXiv:1212.0975v22012
SPlit: An Optimal Method for Data Splitting
V. Roshan Joseph, Akhil Vakayil
stat.MLcs.LGarXiv:2012.10945v22020
Learning and Evaluating General Linguistic Intelligence
Dani Yogatama, Cyprien de Masson d'Autume, Jerome Connor +8
cs.LGcs.CLstat.MLarXiv:1901.11373v12019
Mean Field Analysis of Neural Networks: A Central Limit Theorem
Justin Sirignano, Konstantinos Spiliopoulos
math.PRmath.STstat.MLarXiv:1808.09372v22018
Regularization Techniques for Learning with Matrices
Sham M. Kakade, Shai Shalev-Shwartz, Ambuj Tewari
cs.LGstat.MLarXiv:0910.0610v22009
Error estimates for spectral convergence of the graph Laplacian on random geometric graphs towards the Laplace--Beltrami operator
Nicolas Garcia Trillos, Moritz Gerlach, Matthias Hein +1
stat.MLmath.APmath.DGarXiv:1801.10108v12018
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step
William Fedus, Mihaela Rosca, Balaji Lakshminarayanan +3
stat.MLcs.LGarXiv:1710.08446v32017
Auto-GNN: Neural Architecture Search of Graph Neural Networks
Kaixiong Zhou, Qingquan Song, Xiao Huang +1
cs.LGstat.MLarXiv:1909.03184v22019
RecSim: A Configurable Simulation Platform for Recommender Systems
Eugene Ie, Chih-wei Hsu, Martin Mladenov +5
cs.LGcs.HCcs.IRarXiv:1909.04847v22019
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem
Andre Wibisono
math.OCcs.ITcs.LGarXiv:1802.08089v22018
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Jang-Hyun Kim, Wonho Choo, Hosan Jeong +1
cs.LGcs.AIcs.CVarXiv:2102.03065v12021
Incoherence-Optimal Matrix Completion
Yudong Chen
cs.ITcs.LGstat.MLarXiv:1310.0154v42013
Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising
Junqi Jin, Chengru Song, Han Li +3
stat.MLcs.AIcs.LGarXiv:1802.09756v22018
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning
Yongchan Kwon, James Zou
cs.LGstat.MLarXiv:2110.14049v22021
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology
Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero +3
cs.LGcs.AIcs.DMarXiv:2302.02941v32023
Benchmarking Batch Deep Reinforcement Learning Algorithms
Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh +1
cs.LGcs.AIstat.MLarXiv:1910.01708v12019
Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods
Daniel Otero Baguer, Johannes Leuschner, Maximilian Schmidt
eess.IVcs.CVcs.LGarXiv:2003.04989v22020
Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics
Vinay V. Ramasesh, Ethan Dyer, Maithra Raghu
cs.LGcs.CVstat.MLarXiv:2007.07400v12020
Tighter Variational Bounds are Not Necessarily Better
Tom Rainforth, Adam R. Kosiorek, Tuan Anh Le +4
stat.MLcs.LGarXiv:1802.04537v32018
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh +2
stat.MLcs.LGarXiv:1803.01113v32018
Model-free Training of End-to-end Communication Systems
Fayçal Ait Aoudia, Jakob Hoydis
cs.ITcs.AIstat.MLarXiv:1812.05929v32018
DART: Dropouts meet Multiple Additive Regression Trees
K. V. Rashmi, Ran Gilad-Bachrach
cs.LGstat.MLarXiv:1505.01866v12015
QEBA: Query-Efficient Boundary-Based Blackbox Attack
Huichen Li, Xiaojun Xu, Xiaolu Zhang +2
cs.LGcs.CVstat.MLarXiv:2005.14137v12020
Wasserstein Fair Classification
Ray Jiang, Aldo Pacchiano, Tom Stepleton +2
stat.MLcs.LGarXiv:1907.12059v12019
Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers
Daniel Liu, Ronald Yu, Hao Su
cs.CVcs.CRcs.LGarXiv:1901.03006v42019
Distributed learning with regularized least squares
Shao-Bo Lin, Xin Guo, Ding-Xuan Zhou
cs.LGstat.MLarXiv:1608.03339v22016
Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods
Deirdre Quillen, Eric Jang, Ofir Nachum +3
cs.ROcs.LGstat.MLarXiv:1802.10264v22018
A deep active learning system for species identification and counting in camera trap images
Mohammad Sadegh Norouzzadeh, Dan Morris, Sara Beery +3
cs.LGcs.CVeess.IVarXiv:1910.09716v12019
Triplet Probabilistic Embedding for Face Verification and Clustering
Swami Sankaranarayanan, Azadeh Alavi, Carlos Castillo +1
cs.CVcs.LGstat.MLarXiv:1604.05417v32016
t-DCF: a Detection Cost Function for the Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification
Tomi Kinnunen, Kong Aik Lee, Hector Delgado +5
eess.AScs.CRcs.SDarXiv:1804.09618v22018
Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning
NhatHai Phan, Xintao Wu, Han Hu +1
cs.CRcs.LGstat.MLarXiv:1709.05750v22017
On the Dimensionality of Word Embedding
Zi Yin, Yuanyuan Shen
cs.LGcs.CLstat.MLarXiv:1812.04224v12018
Hypothesis Testing for Automated Community Detection in Networks
Peter J. Bickel, Purnamrita Sarkar
stat.MLcs.LGcs.SIarXiv:1311.2694v22013
On the Error of Random Fourier Features
Danica J. Sutherland, Jeff Schneider
cs.LGstat.MLarXiv:1506.02785v12015
BayesNAS: A Bayesian Approach for Neural Architecture Search
Hongpeng Zhou, Minghao Yang, Jun Wang +1
cs.LGstat.MLarXiv:1905.04919v22019
Few-shot classification in Named Entity Recognition Task
Alexander Fritzler, Varvara Logacheva, Maksim Kretov
cs.CLcs.LGstat.MLarXiv:1812.06158v12018
Robust Learning with Jacobian Regularization
Judy Hoffman, Daniel A. Roberts, Sho Yaida
stat.MLcs.LGarXiv:1908.02729v12019
Path-Level Network Transformation for Efficient Architecture Search
Han Cai, Jiacheng Yang, Weinan Zhang +2
cs.LGcs.AIstat.MLarXiv:1806.02639v12018
On the regularization of Wasserstein GANs
Henning Petzka, Asja Fischer, Denis Lukovnikov
stat.MLcs.LGarXiv:1709.08894v32017
Directional convergence and alignment in deep learning
Ziwei Ji, Matus Telgarsky
cs.LGcs.NEmath.OCarXiv:2006.06657v22020

Machine Learning (stat)

Functional Regularisation for Continual Learning with Gaussian Processes

Recurrent Quantum Neural Networks

Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness

Convolutional Dictionary Learning: A Comparative Review and New Algorithms

DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks

Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification

Gradient Descent Converges to Minimizers

Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion

Efficiently learning Ising models on arbitrary graphs

Parsimonious module inference in large networks

ABC random forests for Bayesian parameter inference

High-dimensional learning of linear causal networks via inverse covariance estimation

Explaining Classifiers with Causal Concept Effect (CaCE)

Datamodels: Predicting Predictions from Training Data

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning

HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing

Exact Global MCMC with Denoising Diffusion

Visualizing the Feature Importance for Black Box Models

Cost-Sensitive Support Vector Machines

SPlit: An Optimal Method for Data Splitting

Learning and Evaluating General Linguistic Intelligence

Mean Field Analysis of Neural Networks: A Central Limit Theorem

Regularization Techniques for Learning with Matrices

Error estimates for spectral convergence of the graph Laplacian on random geometric graphs towards the Laplace--Beltrami operator

Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step

Auto-GNN: Neural Architecture Search of Graph Neural Networks

RecSim: A Configurable Simulation Platform for Recommender Systems

Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem

Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity

Incoherence-Optimal Matrix Completion

Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising

Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning

On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology

Benchmarking Batch Deep Reinforcement Learning Algorithms

Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods

Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics

Tighter Variational Bounds are Not Necessarily Better

Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD

Model-free Training of End-to-end Communication Systems

DART: Dropouts meet Multiple Additive Regression Trees

QEBA: Query-Efficient Boundary-Based Blackbox Attack

Wasserstein Fair Classification

Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers

Distributed learning with regularized least squares

Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods

A deep active learning system for species identification and counting in camera trap images

Triplet Probabilistic Embedding for Face Verification and Clustering

t-DCF: a Detection Cost Function for the Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification

Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning

On the Dimensionality of Word Embedding

Hypothesis Testing for Automated Community Detection in Networks

On the Error of Random Fourier Features

BayesNAS: A Bayesian Approach for Neural Architecture Search

Few-shot classification in Named Entity Recognition Task

Robust Learning with Jacobian Regularization

Path-Level Network Transformation for Efficient Architecture Search

On the regularization of Wasserstein GANs

Directional convergence and alignment in deep learning