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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361 to 420 of 6,772

Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges
Rob Ashmore, Radu Calinescu, Colin Paterson
cs.LGcs.SEstat.MLarXiv:1905.04223v12019
A Multi-Objective Deep Reinforcement Learning Framework
Thanh Thi Nguyen, Ngoc Duy Nguyen, Peter Vamplew +3
cs.LGcs.AIstat.MLarXiv:1803.02965v32018
Semi-Supervised and Task-Driven Data Augmentation
Krishna Chaitanya, Neerav Karani, Christian Baumgartner +3
cs.CVcs.LGstat.MLarXiv:1902.05396v22019
PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making
Fangkai Yang, Daoming Lyu, Bo Liu +1
cs.LGcs.AIstat.MLarXiv:1804.07779v32018
Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network
Weiqi Ji, Sili Deng
q-bio.MNcs.LGphysics.chem-pharXiv:2002.09062v22020
Complete Dictionary Recovery over the Sphere II: Recovery by Riemannian Trust-region Method
Ju Sun, Qing Qu, John Wright
cs.ITcs.CVmath.OCarXiv:1511.04777v32015
MR image reconstruction using deep density priors
Kerem C. Tezcan, Christian F. Baumgartner, Roger Luechinger +2
cs.CVeess.IVstat.MLarXiv:1711.11386v42017
Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices
Tayfun Gokmen, O. Murat Onen, Wilfried Haensch
cs.LGcs.NEstat.MLarXiv:1705.08014v12017
Fairness risk measures
Robert C. Williamson, Aditya Krishna Menon
cs.LGstat.MLarXiv:1901.08665v12019
Limitations of Lazy Training of Two-layers Neural Networks
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz +1
stat.MLcs.LGmath.STarXiv:1906.08899v12019
An analytic theory of generalization dynamics and transfer learning in deep linear networks
Andrew K. Lampinen, Surya Ganguli
stat.MLcs.LGarXiv:1809.10374v22018
Quadratic Autoencoder (Q-AE) for Low-dose CT Denoising
Fenglei Fan, Hongming Shan, Mannudeep K. Kalra +6
cs.LGeess.SPstat.MLarXiv:1901.05593v52019
Privacy in Deep Learning: A Survey
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma +3
cs.LGcs.CRstat.MLarXiv:2004.12254v52020
Sparse and Unique Nonnegative Matrix Factorization Through Data Preprocessing
Nicolas Gillis
stat.MLmath.NAmath.OCarXiv:1204.2436v12012
Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems
Christopher De Sa, Kunle Olukotun, Christopher Ré
cs.LGmath.OCstat.MLarXiv:1411.1134v32014
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent
Trevor Campbell, Tamara Broderick
stat.MLcs.LGstat.COarXiv:1802.01737v22018
Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques
Kundan Krishna, Sopan Khosla, Jeffrey P. Bigham +1
cs.CLcs.AIcs.LGarXiv:2005.01795v32020
Diagnosing Bottlenecks in Deep Q-learning Algorithms
Justin Fu, Aviral Kumar, Matthew Soh +1
cs.LGstat.MLarXiv:1902.10250v12019
Model Selection for Gaussian Mixture Models
Tao Huang, Heng Peng, Kun Zhang
stat.MEmath.STstat.MLarXiv:1301.3558v12013
From optimal transport to generative modeling: the VEGAN cookbook
Olivier Bousquet, Sylvain Gelly, Ilya Tolstikhin +2
stat.MLarXiv:1705.07642v12017
Learning GFlowNets from partial episodes for improved convergence and stability
Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov +6
cs.LGstat.MLarXiv:2209.12782v32022
Reducing Noise in GAN Training with Variance Reduced Extragradient
Tatjana Chavdarova, Gauthier Gidel, François Fleuret +1
stat.MLcs.LGmath.OCarXiv:1904.08598v32019
SCALOR: Generative World Models with Scalable Object Representations
Jindong Jiang, Sepehr Janghorbani, Gerard de Melo +1
cs.LGstat.MLarXiv:1910.02384v42019
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

Machine Learning (stat)

Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges

A Multi-Objective Deep Reinforcement Learning Framework

Semi-Supervised and Task-Driven Data Augmentation

PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making

Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network

Complete Dictionary Recovery over the Sphere II: Recovery by Riemannian Trust-region Method

MR image reconstruction using deep density priors

Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices

Fairness risk measures

Limitations of Lazy Training of Two-layers Neural Networks

An analytic theory of generalization dynamics and transfer learning in deep linear networks

Quadratic Autoencoder (Q-AE) for Low-dose CT Denoising

Privacy in Deep Learning: A Survey

Sparse and Unique Nonnegative Matrix Factorization Through Data Preprocessing

Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems

Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent

Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques

Diagnosing Bottlenecks in Deep Q-learning Algorithms

Model Selection for Gaussian Mixture Models

From optimal transport to generative modeling: the VEGAN cookbook

Learning GFlowNets from partial episodes for improved convergence and stability

Reducing Noise in GAN Training with Variance Reduced Extragradient

SCALOR: Generative World Models with Scalable Object Representations

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