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Statsitical Learning Theory
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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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S&DS Seminar: Jingfeng Wu (Berkeley), “Gradient Descent Dominates Ridge: A Statistical View on Implicit Regularization”
Talk summary: A key puzzle in deep learning is how simple gradient methods find generalizable solutions without explicit regularization. This talk discusses the implicit […]
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FDS Colloquium: Bento Natura (Columbia), “Faster Exact Linear Programming”
Optional Zoom link: https://yale.zoom.us/j/99342713421 Abstract: We present a novel algorithm to solve various subclasses of linear programs, with a particular focus on strongly polynomial […]