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• Feb

  14

  CS Seminar: Modeling Uncertainty for Designing Efficient Algorithms for Machine Learning (Abhishek Shetty)

  Department of Computer Science (CS)

  12:00 PM 3514, Mudd Hall ( formerly Seeley G. Mudd Library)

  EVENT DETAILS

  Wednesday / CS Seminar
  February 14th / 12:00 PM
  In Person / Mudd 3514

  Speaker
  Abhishek Shetty, University of California at Berkeley

  Talk Title
  Modeling Uncertainty for Designing Efficient Algorithms for Machine Learning

  Abstract

  Though modern machine learning has been highly successful, as we move towards more critical applications, many challenges towards ensuring robustness, privacy, and fairness, arise. Ad hoc and empirical approaches have often led to unintended consequences for these objectives, thus necessitating a principled approach. Traditional solutions often require redesigning entire pipelines or come with a significant loss in quality. In this talk, we will look at principles for modeling data towards can incorporating these important desiderata into existing pipelines without significant computational and statistical overhead.

  We will see two vignettes of this line of research. First, the smoothed adversary model for sequential decision making, leading to statistically and computationally efficient algorithms for decision making under uncertainty. Second, we will see a nearly linear-time algorithm for distribution compression leading to improved computational efficiency in diverse downstream statistical tasks.

  Biography
  Abhishek Shetty is currently a PhD student in the Department of Computer Science at the University of California at Berkeley advised by Nika Haghtalab. His research focuses on designing mathematical frameworks bringing together the theory and practice of machine learning and using these to developing simple algorithms with provable guarantees on real-world data. His research has been awarded a American Statistical Association SCSG best student paper award and also the Apple AI/ML fellowship.

  Research Interests/Area
  Theory/Machine Learning

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  TIME Wednesday, February 14, 2024 at 12:00 PM - 1:00 PM

  LOCATION 3514, Mudd Hall ( formerly Seeley G. Mudd Library)    map it

  ADD TO CALENDAR

  CONTACT Wynante R Charles    wynante.charles@northwestern.edu EMAIL

  CALENDAR Department of Computer Science (CS)