Hoang Phuc Hau Luu

According to our database, Hoang Phuc Hau Luu authored at least 17 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

DC-LA: Difference-of-Convex Langevin Algorithm.

Hoang Phuc Hau Luu, Zhongjian Wang

CoRR, January, 2026

2025

Geodesic Slice Sampler for Multimodal Distributions with Strong Curvature.

Bernardo Williams, Hanlin Yu, Hoang Phuc Hau Luu, Georgios Arvanitidis, Arto Klami

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold.

Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams, Marcelo Hartmann, Arto Klami

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

GRADSTOP: Early Stopping of Gradient Descent via Posterior Sampling.

Arash Jamshidi, Lauri Seppäläinen, Katsiaryna Haitsiukevich, Hoang Phuc Hau Luu, Anton Björklund, Kai Puolamäki

Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

2024

Online Stochastic DCA With Applications to Principal Component Analysis.

Hoai An Le Thi, Hoang Phuc Hau Luu, Tao Pham Dinh

IEEE Trans. Neural Networks Learn. Syst., May, 2024

Markov chain stochastic DCA and applications in deep learning with PDEs regularization.

Hoang Phuc Hau Luu, Hoai Minh Le, Hoai An Le Thi

Neural Networks, 2024

Gradient Boosting Mapping for Dimensionality Reduction and Feature Extraction.

Anri Patron, Ayush Prasad, Hoang Phuc Hau Luu, Kai Puolamäki

CoRR, 2024

Non-geodesically-convex optimization in the Wasserstein space.

Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams, Petrus Mikkola, Marcelo Hartmann, Kai Puolamäki, Arto Klami

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Fast and Understandable Nonlinear Supervised Dimensionality Reduction.

Anri Patron, Rafael Savvides, Lauri Franzon, Hoang Phuc Hau Luu, Kai Puolamäki

Proceedings of the Discovery Science - 27th International Conference, 2024

Error bounds for any regression model using Gaussian processes with gradient information.

Rafael Savvides, Hoang Phuc Hau Luu, Kai Puolamäki

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

DCA-Based Weighted Bagging: A New Ensemble Learning Approach.

Van Tuan Pham, Hoai An Le Thi, Hoang Phuc Hau Luu, Pascal Damel

Proceedings of the Intelligent Information and Database Systems - 15th Asian Conference, 2023

2022

Stochastic Difference-of-Convex-Functions Algorithms for Nonconvex Programming.

Hoai An Le Thi, Ngai Van Huynh, Tao Pham Dinh, Hoang Phuc Hau Luu

SIAM J. Optim., September, 2022

Advanced machine learning techniques based on DCA and applications to predictive maintenance. (Techniques avancées d'apprentissage automatique basées sur DCA et applications à la maintenance prédictive).

Hoang Phuc Hau Luu

PhD thesis, 2022

Stochastic DCA with Variance Reduction and Applications in Machine Learning.

Hoai An Le Thi, Hoang Phuc Hau Luu, Hoai Minh Le, Tao Pham Dinh

J. Mach. Learn. Res., 2022

A DC programming approach for solving a centralized group key management problem.

Hoai An Le Thi, Thi Tuyet Trinh Nguyen, Hoang Phuc Hau Luu

J. Comb. Optim., 2022

A Block Coordinate DCA Approach for Large-Scale Kernel SVM.

Van Tuan Pham, Hoang Phuc Hau Luu, Hoai An Le Thi

Proceedings of the Computational Collective Intelligence - 14th International Conference, 2022

2021

Solving a Centralized Dynamic Group Key Management Problem by an Optimization Approach.

Thi Tuyet Trinh Nguyen, Hoang Phuc Hau Luu, Hoai An Le Thi

Proceedings of the Modelling, Computation and Optimization in Information Systems and Management Sciences - Proceedings of the 4th International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, 2021