Abstract:
This talk will explore multiple fascinating facets of centralized and decentralized modeling approaches in machine learning and AI, including large language, vision, and multimodal models. We will in particular discuss disparities in predictive models as well as imbalances in data collections.
Zaid Harchaoui is a Professor at the University of Washington in Seattle, in the Department of Statistics and in the Allen School of Computer Science and Engineering, and a Senior Data Science Fellow in the eScience Institute. He is an action editor at the Journal of Machine Learning Research. He is a principal investigator and a cofounder of IFML, the NSF-AI Institute on Foundations of Machine Learning, and of IFDS, the NSF-TRIPODS institute on foundations of data science.
