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Justin Li is a PhD student at NYU, advised by Matus Telgarsky. He is broadly interested in machine learning theory.
Medha Agarwal is a PhD student in the Department of Statistics at the University of Washington in Seattle, advised by Prof. Zaid Harchaoui. Her research interests are in learning theory and probability theory, and the interplay of the two.
The boot camp is intended to acquaint program participants with the key themes of the program. It will consist of five days of tutorial presentations. If you require special accommodation, please contact our access coordinator at simonsevents [at] berkeley.edu...
This bootcamp talk will be an overview on testing Boolean functions. A Boolean function is a function which maps inputs of a domain to {0, 1} (in other words, encoding a subset of the domain) and the task in property testing is to approximately determine whether the function has a particular property. We aim for algorithms which are really, really efficient (think constant or poly-logarithmic queries to the function). We will cover the definitions of (standard) property testing and some variants, as well as some of the well-known algorithms and analyzes.