Qing Guo
Virginia Tech
Variational Mutual Information Estimation: from Data Collection to Large Vision-Language Models
In today's digital landscape, the deluge of data across various domains can easily overwhelm traditional learning methods to extract useful information. Central to these challenges is the efficient quantification of general associations between variable pairs, and the accurate utilization of this information in decision-making processes. In my talk, I will delve into the critical role of Mutual Information (MI) in modern data science and discuss scaling MI estimation with deep neural networks to address the complexity of contemporary datasets. Specifically, I will present our recent work proposing a novel MI estimation framework powered by variational inference, contrastive estimation, and convex optimization. The proposed method provides theoretical guarantees on the convergence of variational non-parametric MI estimates and features simple implementations. The effectiveness of the proposed method will be elaborated in several applications, including Bayesian optimal data collection, self-supervised learning, conversational recommendation systems, and large vision language models.
Bio: Qing Guo is from Department of Statistics at Virginia Tech (VT). She is also a member of VT Statistics and Artificial Intelligence Laboratory (VT-SAIL). In 2022, she was honored as an Amazon Fellow. Her research focuses on addressing some of the fundamental challenges in machine learning using novel mathematical and statistical insights, with both theoretical analysis and efficient algorithms. Her current focus revolves around enhancing the data efficiency and robustness of artificial intelligence systems through the integration of ideas from information theory. Her research encompasses various topics that comprehensively span the life cycle of AI models, including Data collection, Generative AI, Self-supervised learning, and Knowledge transfer.
DATE: Tuesday, 1/30/24, 3:30 PM, AUST 105
Webex link: https://uconn-cmr.webex.com/uconn-cmr/j.php?MTID=m4112540201db2477fbc38527e560bea6
Coffee will be served at 3:00 pm in the Noether Lounge (AUST 326)
For more information, contact: Tracy Burke at tracy.burke@uconn.edu