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Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function

Mathematical programming, 2014-04, Vol.144 (1-2), p.1-38

2014

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Parallel coordinate descent methods for big data optimization

Mathematical programming, 2016-03, Vol.156 (1-2), p.433-484

2016

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Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting

IEEE journal of selected topics in signal processing, 2016-03, Vol.10 (2), p.242-255

2016

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MagBERT: Magnetics Knowledge Aware Language Model Coupled with a Question Answering Pipeline for Curie Temperature Extraction Task

Journal of physical chemistry. C, 2024-08, Vol.128 (31), p.13217-13229

2024

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Distributed optimization with arbitrary local solvers

Optimization methods & software, 2017-07, Vol.32 (4), p.813-848

2017

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Applying deep learning to the newsvendor problem

IIE transactions, 2020-04, Vol.52 (4), p.444-463

2020

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A Deep Q-Network for the Beer Game: Deep Reinforcement Learning for Inventory Optimization

Manufacturing & service operations management, 2022-01, Vol.24 (1), p.285-304

2022

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Random-reshuffled SARAH does not need full gradient computations

Optimization letters, 2024-04, Vol.18 (3), p.727-749

2024

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Convolutional Neural Network Approach for Robust Structural Damage Detection and Localization

Journal of computing in civil engineering, 2019-05, Vol.33 (3)

2019

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DynNet: Physics-based neural architecture design for nonlinear structural response modeling and prediction

Engineering structures, 2021-02, Vol.229, p.111582, Article 111582

2021

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On optimal probabilities in stochastic coordinate descent methods

Optimization letters, 2016-08, Vol.10 (6), p.1233-1243

2016

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A robust multi-batch L-BFGS method for machine learning

Optimization methods & software, 2020-01, Vol.35 (1), p.191-219

2020

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Structural sensing with deep learning: Strain estimation from acceleration data for fatigue assessment

Computer-aided civil and infrastructure engineering, 2020-12, Vol.35 (12), p.1349-1364

2020

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A low-rank coordinate-descent algorithm for semidefinite programming relaxations of optimal power flow

Optimization methods & software, 2017-07, Vol.32 (4), p.849-871

2017

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Matrix completion under interval uncertainty

European journal of operational research, 2017-01, Vol.256 (1), p.35-43

2017

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Inexact SARAH algorithm for stochastic optimization

Optimization methods & software, 2021-01, Vol.36 (1), p.237-258

2021

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Modal Identification of Bridges Using Mobile Sensors with Sparse Vibration Data

Journal of engineering mechanics, 2020-04, Vol.146 (4)

2020

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Reinforcement Learning Approach to Stochastic Vehicle Routing Problem With Correlated Demands

IEEE access, 2023, Vol.11, p.87958-87969

2023

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Stochastic Gradient Methods with Preconditioned Updates

Journal of optimization theory and applications, 2024-05, Vol.201 (2), p.471-489

2024

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Inexact tensor methods and their application to stochastic convex optimization

Optimization methods & software, 2024-01, Vol.39 (1), p.42-83

2024

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Uncertainty quantification in digital image correlation for experimental evaluation of deep learning based damage diagnostic

Structure and infrastructure engineering, 2021-10, Vol.17 (11), p.1459-1473

2021

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Suppressing Poisoning Attacks on Federated Learning for Medical Imaging

Medical Image Computing and Computer Assisted Intervention – MICCAI 2022, p.673-683

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On the complexity of parallel coordinate descent

Optimization methods & software, 2018-03, Vol.33 (2), p.372-395

2018

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Hybrid Methods in Solving Alternating-Current Optimal Power Flows

IEEE transactions on smart grid, 2017-11, Vol.8 (6), p.2988-2998

2017

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A deep neural network for oxidative coupling of methane trained on high-throughput experimental data

JPhys Energy, 2023-01, Vol.5 (1), p.14009

2023

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Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function

Parallel coordinate descent methods for big data optimization

Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting

MagBERT: Magnetics Knowledge Aware Language Model Coupled with a Question Answering Pipeline for Curie Temperature Extraction Task

Distributed optimization with arbitrary local solvers

Applying deep learning to the newsvendor problem

A Deep Q-Network for the Beer Game: Deep Reinforcement Learning for Inventory Optimization

Random-reshuffled SARAH does not need full gradient computations

Convolutional Neural Network Approach for Robust Structural Damage Detection and Localization

DynNet: Physics-based neural architecture design for nonlinear structural response modeling and prediction

On optimal probabilities in stochastic coordinate descent methods

A robust multi-batch L-BFGS method for machine learning

Structural sensing with deep learning: Strain estimation from acceleration data for fatigue assessment

A low-rank coordinate-descent algorithm for semidefinite programming relaxations of optimal power flow

Matrix completion under interval uncertainty

Inexact SARAH algorithm for stochastic optimization

Modal Identification of Bridges Using Mobile Sensors with Sparse Vibration Data

Reinforcement Learning Approach to Stochastic Vehicle Routing Problem With Correlated Demands

Stochastic Gradient Methods with Preconditioned Updates

Inexact tensor methods and their application to stochastic convex optimization

Uncertainty quantification in digital image correlation for experimental evaluation of deep learning based damage diagnostic

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging

On the complexity of parallel coordinate descent

Hybrid Methods in Solving Alternating-Current Optimal Power Flows

A deep neural network for oxidative coupling of methane trained on high-throughput experimental data

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