Dzung T. Phan

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 42

Top Topics

Convergence Analysis

Multivariate Decision Trees

Objective Function

Top Venues

Publications

Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam, Chandra Reddy
Multi-polytope Machine for Classification. SDM (2024)
Tsuyoshi Idé, Dzung T. Phan, Rudy Raymond
Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis. CoRR (2024)
Quan M. Tran, Suong N. Hoang, Lam M. Nguyen, Dzung T. Phan, Hoang Thanh Lam
TabularFM: An Open Framework For Tabular Foundational Models. CoRR (2024)
Vinícius Lima, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam
Optimal Control via Linearizable Deep Learning. ACC (2023)
Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy
Interpretable Clustering via Multi-Polytope Machines. AAAI (2022)
Tsuyoshi Idé, Georgios Kollias, Dzung T. Phan, Naoki Abe
Cardinality-Regularized Hawkes-Granger Model. CoRR (2022)
Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
A hybrid stochastic optimization framework for composite nonconvex optimization. Math. Program. 191 (2) (2022)
Dzung T. Phan, Hongsheng Liu, Lam M. Nguyen
StepDIRECT - A Derivative-Free Optimization Method for Stepwise Functions. SDM (2022)
Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam
Finite-sum smooth optimization with SARAH. Comput. Optim. Appl. 82 (3) (2022)
Jayant Kalagnanam, Dzung T. Phan, Pavankumar Murali, Lam M. Nguyen, Nianjun Zhou, Dharmashankar Subramanian, Raju Pavuluri, Xiang Ma, Crystal Lui, Giovane Cesar Da Silva
AI-Based Real-Time Site-Wide Optimization for Process Manufacturing. INFORMS J. Appl. Anal. 52 (4) (2022)
Akshay Rangamani, Nam H. Nguyen, Abhishek Kumar, Dzung T. Phan, Sang Peter Chin, Trac D. Tran
A Scale Invariant Measure of Flatness for Deep Network Minima. ICASSP (2021)
Tsuyoshi Idé, Georgios Kollias, Dzung T. Phan, Naoki Abe
Cardinality-Regularized Hawkes-Granger Model. NeurIPS (2021)
Lam M. Nguyen, Quoc Tran-Dinh, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk
A Unified Convergence Analysis for Shuffling-Type Gradient Methods. J. Mach. Learn. Res. 22 (2021)
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
Federated Learning with Randomized Douglas-Rachford Splitting Methods. CoRR (2021)
Thanh Lam Hoang, Gabriele Picco, Yufang Hou, Young-Suk Lee, Lam M. Nguyen, Dzung T. Phan, Vanessa López, Ramón Fernandez Astudillo
Ensembling Graph Predictions for AMR Parsing. NeurIPS (2021)
Hoang Thanh Lam, Gabriele Picco, Yufang Hou, Young-Suk Lee, Lam M. Nguyen, Dzung T. Phan, Vanessa López, Ramón Fernandez Astudillo
Ensembling Graph Predictions for AMR Parsing. CoRR (2021)
Dzung T. Phan, Lam M. Nguyen, Pavankumar Murali, Nhan H. Pham, Hongsheng Liu, Jayant R. Kalagnanam
Regression Optimization for System-level Production Control. ACC (2021)
Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
FedDR - Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization. NeurIPS (2021)
Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy
Interpretable Clustering via Multi-Polytope Machines. CoRR (2021)
Dzung T. Phan, Matt Menickelly
-Constrained Sparse Inverse Covariance Estimation Problems. INFORMS J. Comput. 33 (2) (2021)
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk, Quoc Tran-Dinh
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning. AISTATS (2020)
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization. J. Mach. Learn. Res. 21 (2020)
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk, Quoc Tran-Dinh
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning. CoRR (2020)
Lam M. Nguyen, Quoc Tran-Dinh, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk
A Unified Convergence Analysis for Shuffling-Type Gradient Methods. CoRR (2020)
Haoran Zhu, Pavankumar Murali, Dzung T. Phan, Lam M. Nguyen, Jayant R. Kalagnanam
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees. CoRR (2020)
Haoran Zhu, Pavankumar Murali, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees. NeurIPS (2020)
Dzung T. Phan, Lam M. Nguyen, Nam H. Nguyen, Jayant R. Kalagnanam
Pruning Deep Neural Networks with $\ell_{0}$-constrained Optimization. ICDM (2020)
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization. CoRR (2019)
Dzung T. Phan, Tsuyoshi Idé
-Regularized Sparsity for Probabilistic Mixture Models. SDM (2019)
Tsuyoshi Idé, Rudy Raymond, Dzung T. Phan
Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks. IJCAI (2019)
Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization. CoRR (2019)
Akshay Rangamani, Nam H. Nguyen, Abhishek Kumar, Dzung T. Phan, Sang H. Chin, Trac D. Tran
A Scale Invariant Flatness Measure for Deep Network Minima. CoRR (2019)
Marten van Dijk, Lam M. Nguyen, Phuong Ha Nguyen, Dzung T. Phan
Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD. ICML (2019)
Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam
Optimal Finite-Sum Smooth Non-Convex Optimization with SARAH. CoRR (2019)
Lam M. Nguyen, Nam H. Nguyen, Dzung T. Phan, Jayant R. Kalagnanam, Katya Scheinberg
When Does Stochastic Gradient Algorithm Work Well? CoRR (2018)
Marten van Dijk, Lam M. Nguyen, Phuong Ha Nguyen, Dzung T. Phan
Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD. CoRR (2018)
Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam
Multi-task Multi-modal Models for Collective Anomaly Detection. ICDM (2017)
Dzung T. Phan, Tsuyoshi Idé, Jayant Kalagnanam, Matt Menickelly, Katya Scheinberg
A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization. ICDM Workshops (2017)
William W. Hager, Dzung T. Phan, Jiajie Zhu
Projection algorithms for nonconvex minimization with application to sparse principal component analysis. J. Glob. Optim. 65 (4) (2016)
Dzung T. Phan, Soumyadip Ghosh
Predicting and mitigating congestion for an electric power system under load and renewable uncertainty. ACC (2016)
Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam
Change Detection Using Directional Statistics. IJCAI (2016)
Kevin Warren, Ron F. Ambrosio, Bei Chen, Yuhui Fu, Soumyadip Ghosh, Dzung T. Phan, Mathieu Sinn, Chunhua Tian, Chandu Visweswariah
Managing uncertainty in electricity generation and demand forecasting. IBM J. Res. Dev. 60 (1) (2016)
Dzung T. Phan, Yada Zhu
Multi-stage optimization for periodic inspection planning of geo-distributed infrastructure systems. Eur. J. Oper. Res. 245 (3) (2015)
Jinjun Xiong, Dzung T. Phan, David Kung
A Resource Supply-Demand based Approach for Automatic MapReduce Job Optimization. HPCC/CSS/ICESS (2015)
Dzung T. Phan, Soumyadip Ghosh
Two-stage stochastic optimization for optimal power flow under renewable generation uncertainty. ACM Trans. Model. Comput. Simul. 24 (1) (2014)
William W. Hager, Dzung T. Phan, Hongchao Zhang
An exact algorithm for graph partitioning. Math. Program. 137 (1-2) (2013)
Dzung T. Phan, Jinjun Xiong, Soumyadip Ghosh
A distributed scheme for fair EV charging under transmission constraints. ACC (2012)
Yunmei Chen, William W. Hager, Feng Huang, Dzung T. Phan, Xiaojing Ye, Wotao Yin
Fast Algorithms for Image Reconstruction with Application to Partially Parallel MR Imaging. SIAM J. Imaging Sci. 5 (1) (2012)
Dzung T. Phan, Jayant Kalagnanam
Distributed methods for solving the security-constrained optimal power flow problem. ISGT (2012)
Dzung T. Phan
Lagrangian Duality and Branch-and-Bound Algorithms for Optimal Power Flow. Oper. Res. 60 (2) (2012)
Dzung T. Phan, Soumyadip Ghosh
A two-stage non-linear program for optimal electrical grid power balance under uncertainty. WSC (2011)
William W. Hager, Dzung T. Phan, Hongchao Zhang
Gradient-Based Methods for Sparse Recovery. SIAM J. Imaging Sci. 4 (1) (2011)
William W. Hager, Dzung T. Phan
An Ellipsoidal Branch and Bound Algorithm for Global Optimization. SIAM J. Optim. 20 (2) (2009)
William W. Hager, Dzung T. Phan, Hongchao Zhang
An exact algorithm for graph partitioning CoRR (2009)