A DC Programming Approach for Sparse Linear Discriminant Analysis. - Phan Duy Nhat; Manh Cuong Nguyen 001; Hoai An Le Thi (ICCSAMA, 2014)

A DC Programming Approach for Sparse Estimation of a Covariance Matrix. - Phan Duy Nhat; Hoai An Le Thi; Tao Pham Dinh (MCO (1), 2015)

A DC Programming Approach for Sparse Optimal Scoring. - Hoai An Le Thi; Phan Duy Nhat (PAKDD (2), 2015)

DC programming and DCA for sparse optimal scoring problem. - Hoai An Le Thi; Phan Duy Nhat (Neurocomputing, 2016)

DCA based algorithms for learning with sparsity in high dimensional setting and stochastical learning. (Algorithmes basés sur la programmation DC et DCA pour l'apprentissage avec la parcimonie et l'apprentissage stochastique en grande dimension). - Phan Duy Nhat (2016)

A Novel Approach for Estimating Multiple Sparse Precision Matrices Using ℓ0, 0 Regularization. - Phan Duy Nhat; Hoai An Le Thi (DSAA, 2017)

Stochastic DCA for Sparse Multiclass Logistic Regression. - Hoai An Le Thi; Hoai Minh Le; Duy Nhat Phan; Bach Tran (ICCSAMA, 2017)

Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification. - Hoai An Le Thi; Hoai Minh Le; Phan Duy Nhat; Bach Tran (ICML, 2017)

Efficient Bi-level Variable Selection and Application to Estimation of Multiple Covariance Matrices. - Phan Duy Nhat; Hoai An Le Thi; Tao Pham Dinh (PAKDD (1), 2017)

DC programming and DCA for sparse Fisher linear discriminant analysis. - Hoai An Le Thi; Phan Duy Nhat (Neural Comput. Appl., 2017)

Sparse Covariance Matrix Estimation by DCA-Based Algorithms. - Phan Duy Nhat; Hoai An Le Thi; Tao Pham Dinh (Neural Comput., 2017)

Accelerated Difference of Convex functions Algorithm and its Application to Sparse Binary Logistic Regression. - Phan Duy Nhat; Hoai Minh Le; Hoai An Le Thi (IJCAI, 2018)

A DCA-Like Algorithm and its Accelerated Version with Application in Data Visualization. - Hoai An Le Thi; Hoai Minh Le; Phan Duy Nhat; Bach Tran (CoRR, 2018)

Group variable selection via ℓp, 0 regularization and application to optimal scoring. - Phan Duy Nhat; Hoai An Le Thi (Neural Networks, 2019)

Stochastic DCA for minimizing a large sum of DC functions with application to multi-class logistic regression. - Hoai An Le Thi; Hoai Minh Le; Duy Nhat Phan; Bach Tran (Neural Networks, 2020)

Novel DCA based algorithms for a special class of nonconvex problems with application in machine learning. - Hoai An Le Thi; Hoai Minh Le; Duy Nhat Phan; Bach Tran (Appl. Math. Comput., 2021)

A Framework of Inertial Alternating Direction Method of Multipliers for Non-Convex Non-Smooth Optimization. - Le Thi Khanh Hien; Duy Nhat Phan; Nicolas Gillis (CoRR, 2021)

Block Alternating Bregman Majorization Minimization with Extrapolation. - Le Thi Khanh Hien; Duy Nhat Phan; Nicolas Gillis; Masoud Ahookhosh; Panagiotis Patrinos (CoRR, 2021)

SpeedyIBL: A Solution to the Curse of Exponential Growth in Instance-Based Learning Models of Decisions from Experience. - Thuy Ngoc Nguyen 001; Duy Nhat Phan; Cleotilde Gonzalez (CoRR, 2021)

DCA based approaches for bi-level variable selection and application for estimate multiple sparse covariance matrices. - Hoai An Le Thi; Duy Nhat Phan; Tao Pham Dinh (Neurocomputing, 2021)

An accelerated IRNN-Iteratively Reweighted Nuclear Norm algorithm for nonconvex nonsmooth low-rank minimization problems. - Duy Nhat Phan; Thuy Ngoc Nguyen 001 (J. Comput. Appl. Math., 2021)

Inertial alternating direction method of multipliers for non-convex non-smooth optimization. - Le Thi Khanh Hien; Duy Nhat Phan; Nicolas Gillis (Comput. Optim. Appl., 2022)

Block Bregman Majorization Minimization with Extrapolation. - Le Thi Khanh Hien; Duy Nhat Phan; Nicolas Gillis; Masoud Ahookhosh; Panagiotis Patrinos (SIAM J. Math. Data Sci., 2022)

Geometric characterizations for strong minima with applications to nuclear norm minimization problems. - Jalal Fadili; Tran Thai An Nghia; Duy Nhat Phan (CoRR, 2023)

An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization. - Le Thi Khanh Hien; Duy Nhat Phan; Nicolas Gillis (J. Mach. Learn. Res., 2023)

Learning in Cooperative Multiagent Systems Using Cognitive and Machine Models. - Thuy Ngoc Nguyen 001; Duy Nhat Phan; Cleotilde Gonzalez (ACM Trans. Auton. Adapt. Syst., 2023)

Advanced Predictive Quality Assessment for Ultrasonic Additive Manufacturing with Deep Learning Model. - Lokendra Poudel; Sushant Jha; Ryan Meeker; Duy Nhat Phan; Rahul Bhowmik (CoRR, 2024)

Scalable AI Framework for Defect Detection in Metal Additive Manufacturing. - Duy Nhat Phan; Sushant Jha; James P. Mavo; Erin L. Lanigan; Linh Nguyen; Lokendra Poudel; Rahul Bhowmik (CoRR, 2024)

Difference-of-Convex Algorithm with Extrapolation for Nonconvex, Nonsmooth Optimization Problems. - Duy Nhat Phan; Hoai An Le Thi (Math. Oper. Res., 2024)

Federated learning with randomized alternating direction method of multipliers and application in training neural networks. - Duy Nhat Phan; Patrick Hytla; Andrew Rice; Thuy Ngoc Nguyen 001 (Neural Networks, 2025)

A Linearized Alternating Direction Multiplier Method for Federated Matrix Completion Problems. - Patrick Hytla; Tran Thai An Nghia; Duy Nhat Phan; Andrew Rice (CoRR, 2025)

A machine learning platform for development of low flammability polymers. - Duy Nhat Phan; Alexander B. Morgan; Lokendra Poudel; Rahul Bhowmik (CoRR, 2025)

Solution Uniqueness of Convex Optimization Problems via the Radial Cone. - Jalal Fadili; Tran Thai An Nghia; Duy Nhat Phan (J. Optim. Theory Appl., 2025)