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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301 to 360 of 6,777

EmbraceNet: A robust deep learning architecture for multimodal classification
Jun-Ho Choi, Jong-Seok Lee
cs.LGstat.MLarXiv:1904.09078v12019
Spectral MLE: Top-$K$ Rank Aggregation from Pairwise Comparisons
Yuxin Chen, Changho Suh
cs.LGcs.DScs.ITarXiv:1504.07218v22015
A Priori Estimates of the Population Risk for Two-layer Neural Networks
Weinan E, Chao Ma, Lei Wu
stat.MLcs.LGmath.STarXiv:1810.06397v32018
Support vector machines on the D-Wave quantum annealer
Dennis Willsch, Madita Willsch, Hans De Raedt +1
cs.LGquant-phstat.MLarXiv:1906.06283v32019
Transferability of Spectral Graph Convolutional Neural Networks
Ron Levie, Wei Huang, Lorenzo Bucci +2
cs.LGstat.MLarXiv:1907.12972v32019
Phases in a class of associative memories via hidden neurons
Toshihiro Ota, Masato Taki
cs.LGcond-mat.dis-nncs.NEarXiv:2609.10976v12026
The Big Data Bootstrap
Ariel Kleiner, Ameet Talwalkar, Purnamrita Sarkar +1
cs.LGstat.MLarXiv:1206.6415v12012
Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models
Jesse Engel, Matthew Hoffman, Adam Roberts
cs.LGcs.NEstat.MLarXiv:1711.05772v22017
Relatively Smart II: Tractable or Semi-Supervised Instance-Optimal Learning
Shaddin Dughmi, Alireza F. Pour
cs.LGstat.MLarXiv:2609.10886v12026
Demystifying Fixed k-Nearest Neighbor Information Estimators
Weihao Gao, Sewoong Oh, Pramod Viswanath
cs.LGcs.ITstat.MLarXiv:1604.03006v22016
Cooperative Training of Descriptor and Generator Networks
Jianwen Xie, Yang Lu, Ruiqi Gao +2
stat.MLcs.CVarXiv:1609.09408v32016
Communication-Efficient Accurate Statistical Estimation
Jianqing Fan, Yongyi Guo, Kaizheng Wang
stat.MLcs.LGmath.OCarXiv:1906.04870v22019
Learning Orthogonal Multi-Index Models Beyond Small Initialization: Incremental Learning, Competitive Dynamics and Symmetry
Mo Zhou, Weihang Xu, Simon S. Du +1
cs.LGstat.MLarXiv:2609.10879v12026
Contextual Parameter Generation for Universal Neural Machine Translation
Emmanouil Antonios Platanios, Mrinmaya Sachan, Graham Neubig +1
cs.CLcs.LGstat.MLarXiv:1808.08493v12018
Optimal Distributed Subsampling for Maximum Quasi-Likelihood Estimators with Massive Data
Jun Yu, HaiYing Wang, Mingyao Ai +1
stat.MEcs.DCstat.COarXiv:2005.10435v32020
Flow Duality and Source Geometry for Categorical Generation
Etrit Haxholli
cs.LGstat.MLarXiv:2609.10863v12026
SparCML: High-Performance Sparse Communication for Machine Learning
Cedric Renggli, Saleh Ashkboos, Mehdi Aghagolzadeh +2
cs.DCstat.MLarXiv:1802.08021v32018
A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements
Romain Lopez, Achille Nazaret, Maxime Langevin +4
cs.LGq-bio.GNstat.MLarXiv:1905.02269v12019
Column Networks for Collective Classification
Trang Pham, Truyen Tran, Dinh Phung +1
cs.LGcs.AIstat.MLarXiv:1609.04508v22016
Conformal PID Control for Time Series Prediction
Anastasios N. Angelopoulos, Emmanuel J. Candes, Ryan J. Tibshirani
cs.LGeess.SYstat.MEarXiv:2307.16895v12023
Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors
Samuel B. Hopkins, Tselil Schramm, Jonathan Shi +1
cs.DScs.CCcs.LGarXiv:1512.02337v22015
Federated Learning Meets Multi-objective Optimization
Zeou Hu, Kiarash Shaloudegi, Guojun Zhang +1
cs.LGstat.MLarXiv:2006.11489v22020
EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL
Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Shane Gu
cs.LGstat.MLarXiv:2007.11091v22020
Sum-of-Squares Polynomial Flow
Priyank Jaini, Kira A. Selby, Yaoliang Yu
cs.LGstat.MLarXiv:1905.02325v22019
The emergence of clusters in self-attention dynamics
Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy +1
cs.LGmath.APstat.MLarXiv:2305.05465v62023
Towards the Generalization of Contrastive Self-Supervised Learning
Weiran Huang, Mingyang Yi, Xuyang Zhao +1
cs.LGcs.AIcs.CVarXiv:2111.00743v42021
Iterative Machine Teaching
Weiyang Liu, Bo Dai, Ahmad Humayun +5
stat.MLcs.LGarXiv:1705.10470v32017
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport
Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn +1
cs.LGmath.OCstat.MLarXiv:1802.08249v22018
Partial Label Learning with Self-Guided Retraining
Lei Feng, Bo An
cs.LGstat.MLarXiv:1902.03045v12019
Conformal Calibration Transfer
Achref Doula
cs.LGstat.MLarXiv:2609.10737v12026
Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses
Carlo Baldassi, Alessandro Ingrosso, Carlo Lucibello +2
cond-mat.dis-nnq-bio.NCstat.MLarXiv:1509.05753v12015
Certifiable Robustness to Graph Perturbations
Aleksandar Bojchevski, Stephan Günnemann
cs.LGcs.CRcs.SIarXiv:1910.14356v22019
The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage
Daniel Galvez, Greg Diamos, Juan Ciro +7
cs.LGstat.MLarXiv:2111.09344v12021
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
Ossama Ahmed, Frederik Träuble, Anirudh Goyal +5
cs.ROcs.LGstat.MLarXiv:2010.04296v22020
Denoising Diffusion Samplers
Francisco Vargas, Will Grathwohl, Arnaud Doucet
cs.LGstat.MLarXiv:2302.13834v22023
Epistemic Neural Networks
Ian Osband, Zheng Wen, Seyed Mohammad Asghari +4
cs.LGcs.AIstat.MLarXiv:2107.08924v82021
Defending Against Model Stealing Attacks with Adaptive Misinformation
Sanjay Kariyappa, Moinuddin K Qureshi
stat.MLcs.CRcs.LGarXiv:1911.07100v12019
Deep Generalized Method of Moments for Instrumental Variable Analysis
Andrew Bennett, Nathan Kallus, Tobias Schnabel
stat.MLcs.LGecon.EMarXiv:1905.12495v22019
Learning a bidirectional mapping between human whole-body motion and natural language using deep recurrent neural networks
Matthias Plappert, Christian Mandery, Tamim Asfour
cs.LGcs.CLcs.ROarXiv:1705.06400v22017
Using machine learning to correct model error in data assimilation and forecast applications
Alban Farchi, Patrick Laloyaux, Massimo Bonavita +1
stat.MLcs.LGphysics.data-anarXiv:2010.12605v22020
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations
Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy +4
cs.LGphysics.chem-phstat.MLarXiv:1908.01425v22019
Deep linear neural networks with arbitrary loss: All local minima are global
Thomas Laurent, James von Brecht
cs.LGstat.MLarXiv:1712.01473v22017
Bayesian Optimization with Machine Learning Algorithms Towards Anomaly Detection
MohammadNoor Injadat, Fadi Salo, Ali Bou Nassif +2
cs.LGcs.NIstat.MLarXiv:2008.02327v12020
Principal Graphs and Manifolds
A. N. Gorban, A. Y. Zinovyev
cs.LGcs.NEstat.MLarXiv:0809.0490v22008
Real-Time Sensor Anomaly Detection and Recovery in Connected Automated Vehicle Sensors
Yiyang Wang, Neda Masoud, Anahita Khojandi
eess.SPstat.MLarXiv:1911.01531v22019
Unbiased split variable selection for random survival forests using maximally selected rank statistics
Marvin N. Wright, Theresa Dankowski, Andreas Ziegler
stat.MLcs.LGarXiv:1605.03391v22016
Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances
Meisam Razaviyayn, Tianjian Huang, Songtao Lu +3
math.OCcs.LGstat.MLarXiv:2006.08141v22020
The Random Feature Model for Input-Output Maps between Banach Spaces
Nicholas H. Nelsen, Andrew M. Stuart
math.NAcs.LGphysics.comp-pharXiv:2005.10224v22020
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
Zonglin Li, Chong You, Srinadh Bhojanapalli +8
cs.LGcs.CLcs.CVarXiv:2210.06313v22022
ECG Arrhythmia Classification Using Transfer Learning from 2-Dimensional Deep CNN Features
Milad Salem, Shayan Taheri, Jiann Shiun-Yuan
cs.LGcs.CVstat.MLarXiv:1812.04693v12018
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't
Weinan E, Chao Ma, Stephan Wojtowytsch +1
cs.LGmath.NAstat.MLarXiv:2009.10713v32020
Cross-Subject Transfer Learning in Human Activity Recognition Systems using Generative Adversarial Networks
Elnaz Soleimani, Ehsan Nazerfard
cs.LGstat.MLarXiv:1903.12489v12019
Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning
Tailai Wen, Roy Keyes
cs.LGcs.CVstat.MLarXiv:1905.13628v12019
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting
Salva Rühling Cachay, Bo Zhao, Hailey Joren +1
cs.LGcs.AIstat.MLarXiv:2306.01984v22023
Label Noise SGD Provably Prefers Flat Global Minimizers
Alex Damian, Tengyu Ma, Jason D. Lee
cs.LGcs.ITmath.OCarXiv:2106.06530v22021
Information Theory: A Tutorial Introduction
James V Stone
cs.ITstat.MLarXiv:1802.05968v32018
Nonlinear Interference Mitigation via Deep Neural Networks
Christian Häger, Henry D. Pfister
cs.ITstat.MLarXiv:1710.06234v12017
Direct-Manipulation Visualization of Deep Networks
Daniel Smilkov, Shan Carter, D. Sculley +2
cs.LGcs.HCstat.MLarXiv:1708.03788v12017
Automated Variational Inference in Probabilistic Programming
David Wingate, Theophane Weber
stat.MLcs.AIcs.LGarXiv:1301.1299v12013
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice
Hongzhou Lin, Julien Mairal, Zaid Harchaoui
stat.MLmath.OCarXiv:1712.05654v22017

Machine Learning (stat)

EmbraceNet: A robust deep learning architecture for multimodal classification

Spectral MLE: Top-$K$ Rank Aggregation from Pairwise Comparisons

A Priori Estimates of the Population Risk for Two-layer Neural Networks

Support vector machines on the D-Wave quantum annealer

Transferability of Spectral Graph Convolutional Neural Networks

Phases in a class of associative memories via hidden neurons

The Big Data Bootstrap

Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models

Relatively Smart II: Tractable or Semi-Supervised Instance-Optimal Learning

Demystifying Fixed k-Nearest Neighbor Information Estimators

Cooperative Training of Descriptor and Generator Networks

Communication-Efficient Accurate Statistical Estimation

Learning Orthogonal Multi-Index Models Beyond Small Initialization: Incremental Learning, Competitive Dynamics and Symmetry

Contextual Parameter Generation for Universal Neural Machine Translation

Optimal Distributed Subsampling for Maximum Quasi-Likelihood Estimators with Massive Data

Flow Duality and Source Geometry for Categorical Generation

SparCML: High-Performance Sparse Communication for Machine Learning

A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements

Column Networks for Collective Classification

Conformal PID Control for Time Series Prediction

Fast spectral algorithms from sum-of-squares proofs: tensor decomposition and planted sparse vectors

Federated Learning Meets Multi-objective Optimization

EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL

Sum-of-Squares Polynomial Flow

The emergence of clusters in self-attention dynamics

Towards the Generalization of Contrastive Self-Supervised Learning

Iterative Machine Teaching

On the Convergence and Robustness of Training GANs with Regularized Optimal Transport

Partial Label Learning with Self-Guided Retraining

Conformal Calibration Transfer

Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses

Certifiable Robustness to Graph Perturbations

The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage

CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Denoising Diffusion Samplers

Epistemic Neural Networks

Defending Against Model Stealing Attacks with Adaptive Misinformation

Deep Generalized Method of Moments for Instrumental Variable Analysis

Learning a bidirectional mapping between human whole-body motion and natural language using deep recurrent neural networks

Using machine learning to correct model error in data assimilation and forecast applications

ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations

Deep linear neural networks with arbitrary loss: All local minima are global

Bayesian Optimization with Machine Learning Algorithms Towards Anomaly Detection

Principal Graphs and Manifolds

Real-Time Sensor Anomaly Detection and Recovery in Connected Automated Vehicle Sensors

Unbiased split variable selection for random survival forests using maximally selected rank statistics

Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances

The Random Feature Model for Input-Output Maps between Banach Spaces

The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers

ECG Arrhythmia Classification Using Transfer Learning from 2-Dimensional Deep CNN Features

Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't

Cross-Subject Transfer Learning in Human Activity Recognition Systems using Generative Adversarial Networks

Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning

DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Label Noise SGD Provably Prefers Flat Global Minimizers

Information Theory: A Tutorial Introduction

Nonlinear Interference Mitigation via Deep Neural Networks

Direct-Manipulation Visualization of Deep Networks

Automated Variational Inference in Probabilistic Programming

Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice