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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1,621 to 1,680 of 6,785

Avoiding Latent Variable Collapse With Generative Skip Models
Adji B. Dieng, Yoon Kim, Alexander M. Rush +1
stat.MLcs.CLcs.LGarXiv:1807.04863v22018
Learning Controllable Fair Representations
Jiaming Song, Pratyusha Kalluri, Aditya Grover +2
cs.LGcs.AIstat.MLarXiv:1812.04218v32018
C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework
Pablo Sprechmann, Ignacio Ramírez, Guillermo Sapiro +1
stat.MLcs.CVarXiv:1006.1346v22010
Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
Sindy Löwe, David Madras, Richard Zemel +1
cs.LGstat.MLarXiv:2006.10833v32020
Neural Operator: Graph Kernel Network for Partial Differential Equations
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli +4
cs.LGmath.NAstat.MLarXiv:2003.03485v12020
A Mean Field View of the Landscape of Two-Layers Neural Networks
Song Mei, Andrea Montanari, Phan-Minh Nguyen
stat.MLcond-mat.stat-mechcs.LGarXiv:1804.06561v22018
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
Yuxin Chen, Emmanuel J. Candes
cs.ITcs.LGmath.NAarXiv:1505.05114v22015
Multigrid with rough coefficients and Multiresolution operator decomposition from Hierarchical Information Games
Houman Owhadi
math.NAcs.AImath.STarXiv:1503.03467v52015
Integer Discrete Flows and Lossless Compression
Emiel Hoogeboom, Jorn W. T. Peters, Rianne van den Berg +1
cs.LGcs.CVstat.MLarXiv:1905.07376v42019
(De)Randomized Smoothing for Certifiable Defense against Patch Attacks
Alexander Levine, Soheil Feizi
cs.LGcs.CVstat.MLarXiv:2002.10733v32020
On Information Gain and Regret Bounds in Gaussian Process Bandits
Sattar Vakili, Kia Khezeli, Victor Picheny
stat.MLcs.ITcs.LGarXiv:2009.06966v32020
Black-Box Reductions for Parameter-free Online Learning in Banach Spaces
Ashok Cutkosky, Francesco Orabona
cs.LGmath.OCstat.MLarXiv:1802.06293v22018
Scalable methods for computing state similarity in deterministic Markov Decision Processes
Pablo Samuel Castro
cs.LGcs.AIstat.MLarXiv:1911.09291v12019
Blocks and Fuel: Frameworks for deep learning
Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin +4
cs.LGcs.NEstat.MLarXiv:1506.00619v12015
Deciding When to Decide: Testing Operational Suboptimality Under Distributional Shift
Minxing Zheng, Holly Wiberg, Shixiang Zhu
stat.MLcs.LGstat.MEarXiv:2608.29465v12026
GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation
Minsuk Kahng, Nikhil Thorat, Duen Horng Chau +2
cs.HCcs.AIcs.LGarXiv:1809.01587v12018
Exploring Representativeness and Informativeness for Active Learning
Bo Du, Zengmao Wang, Lefei Zhang +4
cs.LGstat.MLarXiv:1904.06685v12019
On-Device Machine Learning: An Algorithms and Learning Theory Perspective
Sauptik Dhar, Junyao Guo, Jiayi Liu +3
cs.LGcs.DCstat.MLarXiv:1911.00623v22019
On the Limitations of Representing Functions on Sets
Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke +2
cs.LGcs.AIcs.NEarXiv:1901.09006v22019
Deep learning for comprehensive forecasting of Alzheimer's Disease progression
Charles K. Fisher, Aaron M. Smith, Jonathan R. Walsh +1
cs.LGq-bio.QMstat.MLarXiv:1807.03876v22018
Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders
Tengfei Ma, Cao Xiao, Jiayu Zhou +1
cs.LGcs.AIstat.MLarXiv:1804.10850v12018
InfoBot: Transfer and Exploration via the Information Bottleneck
Anirudh Goyal, Riashat Islam, Daniel Strouse +5
stat.MLcs.LGarXiv:1901.10902v52019
SCROLLS: Standardized CompaRison Over Long Language Sequences
Uri Shaham, Elad Segal, Maor Ivgi +8
cs.CLcs.AIcs.LGarXiv:2201.03533v22022
Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms
Tengchan Zeng, Omid Semiari, Mohammad Mozaffari +3
cs.LGcs.ITcs.ROarXiv:2002.08196v22020
Modeling Documents with Deep Boltzmann Machines
Nitish Srivastava, Ruslan R Salakhutdinov, Geoffrey E. Hinton
cs.LGcs.IRstat.MLarXiv:1309.6865v12013
mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions
Bernd Bischl, Jakob Richter, Jakob Bossek +3
stat.MLarXiv:1703.03373v32017
The Disparate Effects of Strategic Manipulation
Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan
cs.LGcs.GTstat.MLarXiv:1808.08646v42018
Topology of deep neural networks
Gregory Naitzat, Andrey Zhitnikov, Lek-Heng Lim
cs.LGmath.ATstat.MLarXiv:2004.06093v12020
Deep Nearest Neighbor Anomaly Detection
Liron Bergman, Niv Cohen, Yedid Hoshen
cs.LGcs.CVstat.MLarXiv:2002.10445v12020
Dual Mixup Regularized Learning for Adversarial Domain Adaptation
Yuan Wu, Diana Inkpen, Ahmed El-Roby
cs.LGcs.CVstat.MLarXiv:2007.03141v22020
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Oran Lang, Yossi Gandelsman, Michal Yarom +8
cs.CVcs.LGcs.NEarXiv:2104.13369v22021
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget
Jaewoo Lee, Daniel Kifer
cs.LGstat.MLarXiv:1808.09501v12018
Gotta Learn Fast: A New Benchmark for Generalization in RL
Alex Nichol, Vicki Pfau, Christopher Hesse +2
cs.LGstat.MLarXiv:1804.03720v22018
A Meta-Analysis of the Anomaly Detection Problem
Andrew Emmott, Shubhomoy Das, Thomas Dietterich +2
cs.AIcs.LGstat.MLarXiv:1503.01158v22015
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup
Sebastian Goldt, Madhu S. Advani, Andrew M. Saxe +2
stat.MLcond-mat.dis-nncond-mat.stat-mecharXiv:1906.08632v22019
Incremental Few-Shot Learning with Attention Attractor Networks
Mengye Ren, Renjie Liao, Ethan Fetaya +1
cs.LGcs.CVstat.MLarXiv:1810.07218v32018
Global Sensitivity Analysis with Dependence Measures
Sébastien Da Veiga
math.STcs.LGstat.MLarXiv:1311.2483v12013
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD
Zeyuan Allen-Zhu
cs.LGcs.DSmath.OCarXiv:1801.02982v32018
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness
Raphael Suter, Đorđe Miladinović, Bernhard Schölkopf +1
stat.MLcs.LGarXiv:1811.00007v22018
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks
Charith Mendis, Alex Renda, Saman Amarasinghe +1
cs.DCcs.LGstat.MLarXiv:1808.07412v22018
Neural Network Matrix Factorization
Gintare Karolina Dziugaite, Daniel M. Roy
cs.LGstat.MLarXiv:1511.06443v22015
Which LLM for Which Work? Budgeted Model Allocation under Uncertain Evaluation
Hamed Khosravi, Xiaoming Huo
cs.LGmath.OCstat.MLarXiv:2608.29560v12026
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Xuanqing Liu, Yao Li, Chongruo Wu +1
cs.LGcs.AIcs.CRarXiv:1810.01279v22018
Convergence of Muon with Newton-Schulz
Gyu Yeol Kim, Min-hwan Oh
stat.MLcs.LGmath.OCarXiv:2601.19156v12026
Online Gate-Driven Flow Control in Resin Transfer Moulding Using a Neural-Network Surrogate
Nicholas Wright, Oliver Maclaren, Piaras Kelly +2
math.OCstat.MLarXiv:2608.29521v12026
Priors in Bayesian Deep Learning: A Review
Vincent Fortuin
stat.MLcs.LGarXiv:2105.06868v32021
Fairness in multi-class multi-group classification problems via contextial coherent risk measures
Darinka Dentcheva, Xiangyu Tian
stat.MLcs.LGarXiv:2608.30223v12026
Building Normalizing Flows with Stochastic Interpolants
Michael S. Albergo, Eric Vanden-Eijnden
cs.LGstat.MLarXiv:2209.15571v32022
Diffusion-GAN: Training GANs with Diffusion
Zhendong Wang, Huangjie Zheng, Pengcheng He +2
cs.LGstat.MLarXiv:2206.02262v42022
Neural Machine Translation and Sequence-to-sequence Models: A Tutorial
Graham Neubig
cs.CLcs.LGstat.MLarXiv:1703.01619v12017
Lossy Image Compression with Compressive Autoencoders
Lucas Theis, Wenzhe Shi, Andrew Cunningham +1
stat.MLcs.CVarXiv:1703.00395v12017
Physics Informed Extreme Learning Machine (PIELM) -- A rapid method for the numerical solution of partial differential equations
Vikas Dwivedi, Balaji Srinivasan
cs.LGphysics.comp-phstat.MLarXiv:1907.03507v12019
Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning
Johnathon Shook, Tryambak Gangopadhyay, Linjiang Wu +3
cs.LGstat.MLarXiv:2006.13847v12020
Provably Efficient Federated Reinforcement Learning with Linear Function Approximation and Logarithmic Communication Cost
Zihang Liang, Haochen Zhang, Lingzhou Xue
stat.MLcs.AIcs.LGarXiv:2609.00193v12026
SGD Learns the Conjugate Kernel Class of the Network
Amit Daniely
cs.LGcs.DSstat.MLarXiv:1702.08503v22017
Multi-Head Attention: Collaborate Instead of Concatenate
Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi
cs.LGcs.CLstat.MLarXiv:2006.16362v22020
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach
Ryo Karakida, Shotaro Akaho, Shun-ichi Amari
stat.MLcond-mat.dis-nncs.LGarXiv:1806.01316v32018
TRACE: Retrospective Streaming Generation of Physical Fields under Sparse Structured Sensing
Xinyu Zhang, Lihao Chen, Panqi Chen +4
stat.MLcs.LGarXiv:2608.26219v12026
Optimization Methods for Large-Scale Machine Learning
Léon Bottou, Frank E. Curtis, Jorge Nocedal
stat.MLcs.LGmath.OCarXiv:1606.04838v32016
Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces
Samuel Daulton, David Eriksson, Maximilian Balandat +1
cs.LGcs.AImath.OCarXiv:2109.10964v42021

Machine Learning (stat)

Avoiding Latent Variable Collapse With Generative Skip Models

Learning Controllable Fair Representations

C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework

Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

Neural Operator: Graph Kernel Network for Partial Differential Equations

A Mean Field View of the Landscape of Two-Layers Neural Networks

Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems

Multigrid with rough coefficients and Multiresolution operator decomposition from Hierarchical Information Games

Integer Discrete Flows and Lossless Compression

(De)Randomized Smoothing for Certifiable Defense against Patch Attacks

On Information Gain and Regret Bounds in Gaussian Process Bandits

Black-Box Reductions for Parameter-free Online Learning in Banach Spaces

Scalable methods for computing state similarity in deterministic Markov Decision Processes

Blocks and Fuel: Frameworks for deep learning

Deciding When to Decide: Testing Operational Suboptimality Under Distributional Shift

GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation

Exploring Representativeness and Informativeness for Active Learning

On-Device Machine Learning: An Algorithms and Learning Theory Perspective

On the Limitations of Representing Functions on Sets

Deep learning for comprehensive forecasting of Alzheimer's Disease progression

Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders

InfoBot: Transfer and Exploration via the Information Bottleneck

SCROLLS: Standardized CompaRison Over Long Language Sequences

Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms

Modeling Documents with Deep Boltzmann Machines

mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions

The Disparate Effects of Strategic Manipulation

Topology of deep neural networks

Deep Nearest Neighbor Anomaly Detection

Dual Mixup Regularized Learning for Adversarial Domain Adaptation

Explaining in Style: Training a GAN to explain a classifier in StyleSpace

Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget

Gotta Learn Fast: A New Benchmark for Generalization in RL

A Meta-Analysis of the Anomaly Detection Problem

Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup

Incremental Few-Shot Learning with Attention Attractor Networks

Global Sensitivity Analysis with Dependence Measures

How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD

Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness

Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks

Neural Network Matrix Factorization

Which LLM for Which Work? Budgeted Model Allocation under Uncertain Evaluation

Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network

Convergence of Muon with Newton-Schulz

Online Gate-Driven Flow Control in Resin Transfer Moulding Using a Neural-Network Surrogate

Priors in Bayesian Deep Learning: A Review

Fairness in multi-class multi-group classification problems via contextial coherent risk measures

Building Normalizing Flows with Stochastic Interpolants

Diffusion-GAN: Training GANs with Diffusion

Neural Machine Translation and Sequence-to-sequence Models: A Tutorial

Lossy Image Compression with Compressive Autoencoders

Physics Informed Extreme Learning Machine (PIELM) -- A rapid method for the numerical solution of partial differential equations

Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning

Provably Efficient Federated Reinforcement Learning with Linear Function Approximation and Logarithmic Communication Cost

SGD Learns the Conjugate Kernel Class of the Network

Multi-Head Attention: Collaborate Instead of Concatenate

Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach

TRACE: Retrospective Streaming Generation of Physical Fields under Sparse Structured Sensing

Optimization Methods for Large-Scale Machine Learning

Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces