Dzung T. Phan

Orcid: 0000-0003-1579-7035

According to our database1, Dzung T. Phan authored at least 43 papers between 2009 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
An End-to-End Time Series Model for Simultaneous Imputation and Forecast.
CoRR, 2023

Optimal Control via Linearizable Deep Learning.
Proceedings of the American Control Conference, 2023

2022
A hybrid stochastic optimization framework for composite nonconvex optimization.
Math. Program., 2022

AI-Based Real-Time Site-Wide Optimization for Process Manufacturing.
INFORMS J. Appl. Anal., 2022

Finite-sum smooth optimization with SARAH.
Comput. Optim. Appl., 2022

StepDIRECT - A Derivative-Free Optimization Method for Stepwise Functions.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Interpretable Clustering via Multi-Polytope Machines.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
A Unified Convergence Analysis for Shuffling-Type Gradient Methods.
J. Mach. Learn. Res., 2021

On the Solution of <i>ℓ</i><sub>0</sub>-Constrained Sparse Inverse Covariance Estimation Problems.
INFORMS J. Comput., 2021

Federated Learning with Randomized Douglas-Rachford Splitting Methods.
CoRR, 2021

FedDR - Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Cardinality-Regularized Hawkes-Granger Model.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Ensembling Graph Predictions for AMR Parsing.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Scale Invariant Measure of Flatness for Deep Network Minima.
Proceedings of the IEEE International Conference on Acoustics, 2021

Regression Optimization for System-level Production Control.
Proceedings of the 2021 American Control Conference, 2021

2020
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization.
J. Mach. Learn. Res., 2020

A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Pruning Deep Neural Networks with $\ell_{0}$-constrained Optimization.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization.
CoRR, 2019

A Scale Invariant Flatness Measure for Deep Network Minima.
CoRR, 2019

Optimal Finite-Sum Smooth Non-Convex Optimization with SARAH.
CoRR, 2019

<i>ℓ</i><sub>0</sub>-Regularized Sparsity for Probabilistic Mixture Models.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
When Does Stochastic Gradient Algorithm Work Well?
CoRR, 2018

2017
A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization.
Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

Multi-task Multi-modal Models for Collective Anomaly Detection.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016
Projection algorithms for nonconvex minimization with application to sparse principal component analysis.
J. Glob. Optim., 2016

Managing uncertainty in electricity generation and demand forecasting.
IBM J. Res. Dev., 2016

Change Detection Using Directional Statistics.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Predicting and mitigating congestion for an electric power system under load and renewable uncertainty.
Proceedings of the 2016 American Control Conference, 2016

2015
Multi-stage optimization for periodic inspection planning of geo-distributed infrastructure systems.
Eur. J. Oper. Res., 2015

A Resource Supply-Demand based Approach for Automatic MapReduce Job Optimization.
Proceedings of the 17th IEEE International Conference on High Performance Computing and Communications, 2015

2014
Two-stage stochastic optimization for optimal power flow under renewable generation uncertainty.
ACM Trans. Model. Comput. Simul., 2014

2013
An exact algorithm for graph partitioning.
Math. Program., 2013

2012
Fast Algorithms for Image Reconstruction with Application to Partially Parallel MR Imaging.
SIAM J. Imaging Sci., 2012

Lagrangian Duality and Branch-and-Bound Algorithms for Optimal Power Flow.
Oper. Res., 2012

Distributed methods for solving the security-constrained optimal power flow problem.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Conference, 2012

A distributed scheme for fair EV charging under transmission constraints.
Proceedings of the American Control Conference, 2012

2011
Gradient-Based Methods for Sparse Recovery.
SIAM J. Imaging Sci., 2011

A two-stage non-linear program for optimal electrical grid power balance under uncertainty.
Proceedings of the Winter Simulation Conference 2011, 2011

2009
An Ellipsoidal Branch and Bound Algorithm for Global Optimization.
SIAM J. Optim., 2009


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