Leaders: PhD. Hoàng Phi Dũng, PTIT; Assoc. PhD. Đỗ Xuân Chợ, PTIT (GG scholar, RG). 

Time: Friday, 9.00 am, Room 105A2, PTIT

Fall 2025: Seminar Networks and Machine learning

Schedule of Fall 2025,

Friday, 15/8/2025 - 9.00 am at 105-A2, PTIT.

Trần Đức Việt Anh (D24 IT - PTIT): Some types of machine learning

Phạm Văn Thành (D24 IT - PTIT): Linear regression

Nguyễn Thành Đạt (D24 Cyb - PTIT): Gradient descent

Friday, 08/8/2025 - 9.00 am at 105-A2, PTIT.

Trần Đức Việt Anh (D24 IT - PTIT): Some types of machine learning

Phạm Văn Thành (D24 IT - PTIT): Linear regression

Nguyễn Thành Đạt (D24 Cyb - PTIT): Gradient descent

Schedule of Fall 2024

Thursday, 24/10/2024 - 9.30 am at 201-A2, PTIT.

9.30 - 10.30 am: Nguyễn Đức Mạnh (D22 IT - PTIT): Minimizing the influence spread over a network through node interception.

Abstract: The optimal node interception strategy during influence propagation over a (directed) network G = (V, A). More specifically, it aims to find an interception set D ⊆ V such that the influence spread over the remaining network G∖D under the linear threshold diffusion model is minimized.

10.30 am: Discussion.

Thursday, 10/10/2024 - 9.30 am at 201-A2, PTIT

9.30 - 10.30 am: Trương Hồng Bảo (Hanoi University): GNNExplainer: Explanations for Graph Neural Networks.

Abstract: Graph Neural Networks (GNNs) are a powerful tool for machine learning on graphs. GNNs combine node feature information with the graph structure by recursively passing neural messages along edges of the input graph. But, graph neural networks did not have a method for explainable predictions and existing neural network explanation frameworks don't work well with graphs. GNNExplainer is a new method for explain the Graph neural network with more accurate.

10.30 am: Discussion.

Thursday, 26/09/2024 - 9.30 am at 206-A2, PTIT

9.30 - 10.00 am: La Quang Hai (D22 CS - PTIT): EM Algorithm for Data Imputation.

Abstract: This report provides an overview of issues related to missing data, the EM algorithm, illustrative examples with normally distributed data, and real-world data. The experimental results in the report are calculated using the Python programming language. Additionally, the report highlights challenges with textual data and proposes feasible solutions 

10.00 am: Discussion. 

Thursday, 29/08/2024 - 9.00 am at 205-A2, PTIT

9.00-9.30 am: Nguyen Khac Gia Hoang (D22 IT - PTIT): An Optimization Algorithm.

Abstract: Gradient descent - a popular optimization algorithm and variants of gradient descent.

9.30 am: Discussion.

Thursday, 22/08/2024 - 9.00 am at 206-A2, PTIT

9.00-9.20 am: Nguyen Thi Hien (D22 IT - PTIT): Logistic regression.

Abstract: In this talk, we will discuss about logistic regression, a fundamental statistical method widely used for binary classification problems.

9.30-10.30 am: Bui Quang Dat (D22 Computer Science - PTIT): Anomaly Detection.

Abstract: Explore anomaly detection techniques to identify unusual data patterns and enhance system reliability.  

Thursday, 15/08/2024 - 9.00 am at 206-A2, PTIT 

9.00-9.30 am: Le Khanh Chi (College of Science and Engineering, University of Minnesota, US): Retrieval-Augmented Generation.

Abstract: In this talk, we will discuss about RAG (Retrieval-Augmented Generation). RAG is an AI framework that combines the strengths of traditional information retrieval systems (such as databases) with the capabilities of generative large language models (LLMs).

10.00-10.20 am: Nguyen Manh Hung (D20 Information Technology-PTIT): 3D View Synthesis: Exploring NeRF and Applications in Real-Time Interactive Virtual Portraits.

10.30 am: Discussion.

Schedule of Summer 2024

Thursday, 01/8/2024

8.30-8.50 am: Nguyen Manh Cong (D23 Security-PTIT), Some probability distributions 2.

9.00-9.30 am: Dao Binh Minh (D23 Computer Science-PTIT): On the Maximum likelihood.

9.30 am: Discussion.

Thursday, 25/7/2024.

8.30-8.50 am: Nguyen Manh Cong (D23 Security-PTIT), Some probability distributions.

9.00-9.45 am: Tran Van Khanh (D23 Information Technology-PTIT): Linear Algebra and Linear regression.

9.55 am: Discussion.

Friday, 19/7/2024:

- 8.30-9.00 am, Registration and Ceremony

- 9.00-9.30 am: Hoàng Phi Dũng (PTIT): Math and AI, the picture

- 9.30-10.00 am: Bùi Quang Đạt, (D22 Computer Science-PTIT): Matrix analysis, gradient of vector-valued function.

- 10.00-10.45 am: Nguyễn Hồng Đức (Master at Tokyo Univ.): Applied Math + AI and problems of self-driving cars.

Abstract. Some problems: Ground segmentation (phân tách mặt phẳng), Simultaneous Localization and Mapping (định vị và lập bản đồ đồng thời), Object detection and tracking (phát hiện và theo dấu vật thể).

10.45: Discussion.