• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    Jube 28, 2022: Dr. Le Duc Trong (VNU Univ. Eng. Tech.), Reliable Machine Learning: Concepts, Approaches and Challenges

    In supervised learning, researchers often discover underlying patterns from a training dataset using ML algorithms. They expect that these patterns could be exploited to facilitate the prediction task on unseen/future data. This expectation maybe met once there exists an i.i.d distribution among seen and unseen dataset. However, it is not always true in various real-life scenarios. In some cases, the performance on training/validation set is pretty good (> 90%) while it is below the acceptant threshold in the testing/unseen set. Another case, the prediction on future data is first working well, but later becomes unreasonable. These problems raise critical questions on the reliabity of the predictive models, e.g., could we completly be confident on the prediction? How to evaluate their reliablity? How to enhance the their reliablity? If the model is unreliable, it is not applicable in resolving real-life tasks. In this talk, the presenter will give a brief introduction about reliable machine learning including basic concepts, challenges and several practical approaches.

    Speaker: Dr. Le Duc Trong, VNU Univ. Eng. Tech.

    Time: 15:30, Tuesday, June, 2022

    Venue: Webinar

    speaker

    Dr Le Duc Trong is currently a lecturer at University of Engineering and Technology, Vietnam National University, Hanoi. He received his bachelor degree in Information Technology from VNU-UET (2011); PhD degree in Information Systems from Singapore Management University (2019). His research interest focuses on recommendation systems, reliable machine learning and social/web mining. His papers are published in the proceedings of top-tier conferences such as AAAI, IJCAI, COLING, ACMM. Beside academic activities, he is also a key member in a number of industrial AI projects in various domains funded by companies and organizations.

    SAME CATEGORY

    February 2, 2024: Dr. Khoa D. Doan (Vin Univeristy) Toward Reliable and Practical Machine Learning Applications

    While Machine Learning (ML) has rapidly transformed several domains and applications with incredible successes, there are also important areas where the progress is significantly slower. Specifically, there exists a widened complexity gap between the methods currently investigated in research and those used in practice in these areas. One reason is that many algorithms, despite achieving […]

    February 2, 2024: Prof. Heng Ji (University of Illinois at Urbana-Champaign), Combating with Misinformation and Cancer: A Unified Multimodal AI Approach to Healthy and Happy Life

    A research overview of ongoing research projects, especially focusing on two that are most related to the VinUni-UIUC Smart Health Center: (1) Misinformation Detection and Trustworthy Large Language Models; (2) Joint Natural Language and Molecule Learning for Drug Discovery. Unsurprisingly these two seemingly different research problems can be tackled with a unified approach based on […]

    January 11, 2024: Dr. Le Duc Trong (FIT-UET) Resilient Multimodal Learning for Multimodal Emotion Recognition in the Presence of Incomplete Modalities

    Multimodal Emotion Recognition in Conversation (Multimodal ERC) is a critical area of research for interpreting human communication in diverse applications. Nevertheless, the persistent issue of uncertain missing modalities poses a major hurdle, hampering the development of robust Multimodal ERC models. Existing approaches face limitations in effectively leveraging a fusion of diverse data modalities encompassing audio, […]