ACM India Webinar Series on Education: Thursday, 29 June, 6:00 pm IST

ACM India Webinar Series on Education: Thursday, 29 June, 6:00 pm IST with Vineeth N. Balasubramanian

"Going Beyond Continual Learning: Towards Organic Lifelong Learning"

The next session of the Education Webinar Series for college and university faculty members is on an interesting topic, which deals with the necessity of the Machine Learning models to continuously adapt and learn from new data so that they can cater to the changing environments.

Register Now for this session of ACM India Webinar Series on Education to be presented on Thursday, 29 June, 6:00 pm IST by Vineeth N Balasubramanian.

Registrations are limited, so please register early and secure your spot.

Note : You can also stream this webinar on your mobile device, including smartphone and tablet.

Abstract: Supervised learning, the harbinger of machine learning over the last decade, has had tremendous impact across application domains in recent years. However, the notion of a static trained machine learning model is becoming increasingly limiting, as these models are deployed in changing and evolving environments. Among a few related settings, continual learning has gained significant interest among practitioners to address this need of continually learning from new information—including new classes, tasks or domains, without losing the model's effectiveness on past data. In this talk, we will briefly discuss lifelong (or continual) learning, and highlight the need to go beyond the vanilla setting to address real-world challenges. In particular, the talk will describe our efforts towards "organic lifelong learning", viz, the ability of a machine learning model to continually learn over time with whatever information or data is available at a given point in time, including the much-needed ability of saying "I don't know." The talk will cover some of our recent research on open-world object detection (CVPR 2021), novel class discovery (ECCV 2022), and continual zero-shot learning (CVPR 2022), besides other work in this domain—and also share interesting real-world use cases of these research efforts.

Duration : 60 minutes (including audience Q&A)

Brief Bio of the Speaker:

Vineeth N Balasubramanian is an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology, Hyderabad (IIT-H), India, and is currently a Fulbright-Nehru Visiting Faculty Fellow at Carnegie Mellon University. He was also the Founding Head of the Department of Artificial Intelligence at IIT-H from 2019–22. His research interests include deep learning, machine learning, and computer vision with a focus on explainability, continual learning and learning with limited labeled data. His research has resulted in over 160 peer-reviewed publications at various international venues, including top-tier venues such as ICML, CVPR, NeurIPS, ICCV, KDD, AAAI, and IEEE TPAMI, with Best Paper Awards at recent venues such as CODS-COMAD 2022, CVPR 2021 Workshop on Causality in Vision, etc. He served as a General Chair for ACML 2022, and serves as a Senior PC/Area Chair regularly for conferences such as CVPR, ICCV, AAAI, IJCAI and ECCV. He is a recipient of the Google Research Scholar Award (2021), NASSCOM AI Gamechanger Award (2022, both recipient and runner-up), Teaching Excellence Award at IIT-H (2017 and 2021), and Research Excellence Award at IIT-H (2022), among others. For more details, please see .

Host: Chitra Babu,

Sri Sivasubramaniya Nadar(SSN) College of Engineering,

Tamil Nadu. INDIA