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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421 to 480 of 6,778

Universal representations:The missing link between faces, text, planktons, and cat breeds
Hakan Bilen, Andrea Vedaldi
cs.CVstat.MLarXiv:1701.07275v12017
Bayesian Batch Active Learning as Sparse Subset Approximation
Robert Pinsler, Jonathan Gordon, Eric Nalisnick +1
stat.MLcs.LGarXiv:1908.02144v42019
Large-scale Interactive Recommendation with Tree-structured Policy Gradient
Haokun Chen, Xinyi Dai, Han Cai +5
cs.LGcs.AIstat.MLarXiv:1811.05869v12018
Building competitive direct acoustics-to-word models for English conversational speech recognition
Kartik Audhkhasi, Brian Kingsbury, Bhuvana Ramabhadran +2
cs.CLcs.AIcs.NEarXiv:1712.03133v12017
Accelerated Mini-Batch Stochastic Dual Coordinate Ascent
Shai Shalev-Shwartz, Tong Zhang
stat.MLcs.LGarXiv:1305.2581v12013
A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem
Lin Xiao, Tong Zhang
math.OCcs.ITstat.MLarXiv:1203.3002v12012
Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset
Martin Mundt, Sagnik Majumder, Sreenivas Murali +2
cs.CVcs.LGstat.MLarXiv:1904.08486v12019
Structured Nonconvex and Nonsmooth Optimization: Algorithms and Iteration Complexity Analysis
Bo Jiang, Tianyi Lin, Shiqian Ma +1
math.OCcs.LGstat.MLarXiv:1605.02408v52016
Optimal Regularization Can Mitigate Double Descent
Preetum Nakkiran, Prayaag Venkat, Sham Kakade +1
cs.LGcs.NEmath.STarXiv:2003.01897v22020
Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization
Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur
stat.MLcs.LGarXiv:1210.1190v12012
Geometrically Convergent Distributed Optimization with Uncoordinated Step-Sizes
Angelia Nedić, Alex Olshevsky, Wei Shi +1
math.OCeess.SYstat.MLarXiv:1609.05877v12016
Generative Models of Visually Grounded Imagination
Ramakrishna Vedantam, Ian Fischer, Jonathan Huang +1
cs.LGcs.CVstat.MLarXiv:1705.10762v82017
Exactly Computing the Local Lipschitz Constant of ReLU Networks
Matt Jordan, Alexandros G. Dimakis
stat.MLcs.LGarXiv:2003.01219v22020
High-recall causal discovery for autocorrelated time series with latent confounders
Andreas Gerhardus, Jakob Runge
stat.MEcs.LGstat.MLarXiv:2007.01884v32020
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
Xiangyi Chen, Sijia Liu, Kaidi Xu +4
cs.LGmath.OCstat.MLarXiv:1910.06513v22019
Stochastic Optimization for Performative Prediction
Celestine Mendler-Dünner, Juan C. Perdomo, Tijana Zrnic +1
cs.LGcs.GTstat.MLarXiv:2006.06887v42020
Trimmed Constrained Mixed Effects Models: Formulations and Algorithms
Peng Zheng, Ryan Barber, Reed J. D. Sorensen +2
stat.MEmath.OCstat.MLarXiv:1909.10700v22019
LoRAS: An oversampling approach for imbalanced datasets
Saptarshi Bej, Narek Davtyan, Markus Wolfien +2
cs.LGstat.MLarXiv:1908.08346v42019
Prodigy: An Expeditiously Adaptive Parameter-Free Learner
Konstantin Mishchenko, Aaron Defazio
cs.LGcs.AImath.OCarXiv:2306.06101v42023
Machine learning for protein folding and dynamics
Frank Noé, Gianni De Fabritiis, Cecilia Clementi
physics.bio-phphysics.chem-phq-bio.BMarXiv:1911.09811v12019
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation
Suraj Nair, Chelsea Finn
cs.LGcs.AIcs.CVarXiv:1909.05829v12019
Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure
Besmira Nushi, Ece Kamar, Eric Horvitz
cs.LGcs.AIcs.HCarXiv:1809.07424v12018
Convolutional RNN: an Enhanced Model for Extracting Features from Sequential Data
Gil Keren, Björn Schuller
stat.MLcs.CLarXiv:1602.05875v32016
Do We Really Need Deep Learning Models for Time Series Forecasting?
Shereen Elsayed, Daniela Thyssens, Ahmed Rashed +2
cs.LGstat.MLarXiv:2101.02118v22021
Krylov Subspace Descent for Deep Learning
Oriol Vinyals, Daniel Povey
stat.MLmath.OCarXiv:1111.4259v12011
Optimum Statistical Estimation with Strategic Data Sources
Yang Cai, Constantinos Daskalakis, Christos H. Papadimitriou
stat.MLcs.GTcs.LGarXiv:1408.2539v22014
Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability
Shaowu Pan, Karthik Duraisamy
math.DSstat.MLarXiv:1906.03663v52019
CubeNet: Equivariance to 3D Rotation and Translation
Daniel Worrall, Gabriel Brostow
cs.CVcs.AIcs.LGarXiv:1804.04458v12018
Maximum Correntropy Unscented Filter
Xi Liu, Badong Chen, Bin Xu +2
stat.MLarXiv:1608.07526v12016
Feature-map-level Online Adversarial Knowledge Distillation
Inseop Chung, SeongUk Park, Jangho Kim +1
cs.LGcs.AIcs.CVarXiv:2002.01775v32020
Why should we add early exits to neural networks?
Simone Scardapane, Michele Scarpiniti, Enzo Baccarelli +1
cs.NEcs.LGstat.MLarXiv:2004.12814v22020
Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification
Zhuoning Yuan, Yan Yan, Milan Sonka +1
cs.LGcs.CVmath.OCarXiv:2012.03173v22020
Reinforcement Learning for Improving Agent Design
David Ha
cs.LGstat.MLarXiv:1810.03779v32018
Drug cell line interaction prediction
Pengfei Liu
q-bio.QMcs.LGstat.MLarXiv:1812.11178v12018
Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations: Column Combining Under Joint Optimization
H. T. Kung, Bradley McDanel, Sai Qian Zhang
cs.LGcs.ARstat.MLarXiv:1811.04770v12018
Semi-Implicit Graph Variational Auto-Encoders
Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield +3
cs.LGstat.MLarXiv:1908.07078v42019
BOCK : Bayesian Optimization with Cylindrical Kernels
ChangYong Oh, Efstratios Gavves, Max Welling
stat.MLcs.LGarXiv:1806.01619v22018
Learning Theory for Distribution Regression
Zoltan Szabo, Bharath Sriperumbudur, Barnabas Poczos +1
math.STcs.LGmath.FAarXiv:1411.2066v42014
Embedding Multimodal Relational Data for Knowledge Base Completion
Pouya Pezeshkpour, Liyan Chen, Sameer Singh
cs.AIcs.CLstat.MLarXiv:1809.01341v22018
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models
Yarin Gal, Mark van der Wilk, Carl E. Rasmussen
stat.MLcs.LGarXiv:1402.1389v22014
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
Sharif Abuadbba, Kyuyeon Kim, Minki Kim +5
cs.CRcs.LGcs.NEarXiv:2003.12365v12020
Distributionally Robust Optimization and Generalization in Kernel Methods
Matthew Staib, Stefanie Jegelka
cs.LGstat.MLarXiv:1905.10943v12019
The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks
Emmanuel Abbe, Enric Boix-Adsera, Theodor Misiakiewicz
cs.LGcs.DSstat.MLarXiv:2202.08658v22022
Does Invariant Risk Minimization Capture Invariance?
Pritish Kamath, Akilesh Tangella, Danica J. Sutherland +1
stat.MLcs.AIcs.LGarXiv:2101.01134v22021
Coupling and Convergence for Hamiltonian Monte Carlo
Nawaf Bou-Rabee, Andreas Eberle, Raphael Zimmer
math.PRstat.COstat.MLarXiv:1805.00452v22018
Quaternion Recurrent Neural Networks
Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid +4
stat.MLcs.LGarXiv:1806.04418v32018
Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie
Rémi Laumont, Valentin de Bortoli, Andrés Almansa +3
stat.MEcs.CVeess.IVarXiv:2103.04715v62021
Unpaired Image-to-Image Translation via Neural Schrödinger Bridge
Beomsu Kim, Gihyun Kwon, Kwanyoung Kim +1
cs.CVcs.AIcs.LGarXiv:2305.15086v32023
LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets
Ang Li, Jingwei Sun, Binghui Wang +4
cs.LGcs.DCstat.MLarXiv:2008.03371v12020
Summaries:한국어
Signature moments to characterize laws of stochastic processes
Ilya Chevyrev, Harald Oberhauser
math.STmath.PRstat.MLarXiv:1810.10971v22018
DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning
Benjamin Shickel, Tyler J. Loftus, Lasith Adhikari +3
cs.LGcs.AIstat.AParXiv:1802.10238v42018
Combinatorial Bayesian Optimization using the Graph Cartesian Product
Changyong Oh, Jakub M. Tomczak, Efstratios Gavves +1
stat.MLcs.LGarXiv:1902.00448v22019
The Conditional Entropy Bottleneck
Ian Fischer
cs.LGstat.MLarXiv:2002.05379v12020
Effective Ways to Build and Evaluate Individual Survival Distributions
Humza Haider, Bret Hoehn, Sarah Davis +1
cs.LGstat.MLarXiv:1811.11347v12018
Likelihood-free inference with nuisance parameters through normalizing flows
Phil Assheton
stat.MEcs.LGstat.MLarXiv:2609.10534v12026
Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction
Mingyuan Zhou
stat.MLcs.SIarXiv:1501.06218v22015
Quantum-Inspired Support Vector Machine
Chen Ding, Tian-Yi Bao, He-Liang Huang
cs.LGcs.CCquant-pharXiv:1906.08902v52019
Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity
Amirhossein Reisizadeh, Isidoros Tziotis, Hamed Hassani +2
cs.LGcs.DCstat.MLarXiv:2012.14453v12020
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT
Philipp Seeböck, José Ignacio Orlando, Thomas Schlegl +5
eess.IVcs.CVcs.LGarXiv:1905.12806v12019
Generalization in Generation: A closer look at Exposure Bias
Florian Schmidt
cs.LGcs.CLstat.MLarXiv:1910.00292v22019

Machine Learning (stat)

Universal representations:The missing link between faces, text, planktons, and cat breeds

Bayesian Batch Active Learning as Sparse Subset Approximation

Large-scale Interactive Recommendation with Tree-structured Policy Gradient

Building competitive direct acoustics-to-word models for English conversational speech recognition

Accelerated Mini-Batch Stochastic Dual Coordinate Ascent

A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem

Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset

Structured Nonconvex and Nonsmooth Optimization: Algorithms and Iteration Complexity Analysis

Optimal Regularization Can Mitigate Double Descent

Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization

Geometrically Convergent Distributed Optimization with Uncoordinated Step-Sizes

Generative Models of Visually Grounded Imagination

Exactly Computing the Local Lipschitz Constant of ReLU Networks

High-recall causal discovery for autocorrelated time series with latent confounders

ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization

Stochastic Optimization for Performative Prediction

Trimmed Constrained Mixed Effects Models: Formulations and Algorithms

LoRAS: An oversampling approach for imbalanced datasets

Prodigy: An Expeditiously Adaptive Parameter-Free Learner

Machine learning for protein folding and dynamics

Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation

Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure

Convolutional RNN: an Enhanced Model for Extracting Features from Sequential Data

Do We Really Need Deep Learning Models for Time Series Forecasting?

Krylov Subspace Descent for Deep Learning

Optimum Statistical Estimation with Strategic Data Sources

Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability

CubeNet: Equivariance to 3D Rotation and Translation

Maximum Correntropy Unscented Filter

Feature-map-level Online Adversarial Knowledge Distillation

Why should we add early exits to neural networks?

Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification

Reinforcement Learning for Improving Agent Design

Drug cell line interaction prediction

Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations: Column Combining Under Joint Optimization

Semi-Implicit Graph Variational Auto-Encoders

BOCK : Bayesian Optimization with Cylindrical Kernels

Learning Theory for Distribution Regression

Embedding Multimodal Relational Data for Knowledge Base Completion

Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models

Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?

Distributionally Robust Optimization and Generalization in Kernel Methods

The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks

Does Invariant Risk Minimization Capture Invariance?

Coupling and Convergence for Hamiltonian Monte Carlo

Quaternion Recurrent Neural Networks

Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie

Unpaired Image-to-Image Translation via Neural Schrödinger Bridge

LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets

Signature moments to characterize laws of stochastic processes

DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning

Combinatorial Bayesian Optimization using the Graph Cartesian Product

The Conditional Entropy Bottleneck

Effective Ways to Build and Evaluate Individual Survival Distributions

Likelihood-free inference with nuisance parameters through normalizing flows

Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction

Quantum-Inspired Support Vector Machine

Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity

Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT

Generalization in Generation: A closer look at Exposure Bias