Newsroom
Machine Learning
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Lu Lu on MIT Technology Review’s Innovators Under 35 list
We are proud to announce that Prof. Lu Lu has been named to the MIT Technology Review’s Innovators Under 35 list for the Asia […]
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Dissertation Defense: Anay Mehrotra, “Learning Theory in the Wild: Foundations of Missing Data and Language Generation”
Abstract: What can be learned from data? This fundamental question in machine learning takes on new complexity in modern pipelines where classical assumptions fail—both […]
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FDS Colloquium: Lorenzo Orecchia (Chicago), “Variational Characterizations of First-Order Algorithms via Self-Duality”
Talk summary: First-order methods for convex optimization play an important role in the efficient deployment of machine learning algorithms. While a large number of […]
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FDS Colloquium: George Lan (Georgia Tech), “Algorithmic Foundations of Risk-averse Optimization for Trustworthy AI”
Talk summary: Over the past two decades, stochastic optimization has made remarkable strides, driving its widespread adoption in machine learning (ML) and artificial intelligence (AI). […]
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FDS Seminar: Akhil Premkumar (UChicago), “An information theoretic view of machine learning”
Abstract: Diffusion models serve as a bridge between generative AI and information theory. These models have demonstrated a remarkable ability to learn high-dimensional continuous distributions, […]