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Robust mean estimation is the following basic estimation question: given i.i.d. copies of a random vector X in d-dimensional Euclidean space of which a small constant fraction are corrupted, how well…
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Samuel Hopkins Date
December 2nd, 2019
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In the 'frequent items' problem one sees a sequence of items in a stream (e.g. a stream of words coming into a search query engine likeGoogle) and wants to report a small list of items…
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Jelani Nelson Date
September 16th, 2019
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This talk focuses on network design algorithms for optimizing average consensus dynamics, dynamics that are widely used for information diffusion and distributed coordination in networked control…
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Yuhao Yi Date
November 18th, 2019
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(This is Part 2, continuation of Tuesday's lecture.)A fundamental tool used in sampling, counting, and inference problems is the Markov Chain Monte Carlo method, which uses random walks to solve…
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Nima Anari Date
November 6th, 2019
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A fundamental tool used in sampling, counting, and inference problems is the Markov Chain Monte Carlo method, which uses random walks to solve computational problems. The main parameter defining the…
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Nima Anari Date
November 5th, 2019
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In this talk we consider random utility models for discrete choice. In discrete choice, the task is to select exactly one element from a discrete set of alternatives. We focus on algorithmic…
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Ravi Kumar Date
November 4th, 2019
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Optimizing neural networks is a highly nonconvex problem, and even optimizing a 2-layer neural network can be challenging. In the recent years many different approaches were proposed to learn 2-layer…
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Rong Ge Date
October 28th, 2019
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In partial function extension, we are given a partial function consisting of points from a domain and a function value at each point.Our objective is to determine if this partial function can be…
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Umang Bhaskar Date
October 18th, 2019
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The Matrix Spencer Conjecture asks whether given n symmetric matrices in ℝn×n with eigenvalues in [−1,1] one can always find signs so that their signed sum has singular values bounded by…
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Thomas Rothvoss Date
October 7th, 2019
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This talk surveys the usage of Lagrangian Duality in the design and analysis of auctions. Designing optimal (revenue maximizing) auctions in multi-parameter settings has been among the most active…
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Nikhil Devanur Date
September 30th, 2019
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Modern online marketplaces feed themselves. They rely on historical data to optimize content and user-interactions, but further, the data generated from these interactions is fed back into the system…
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Shipra Agrawal Date
September 23rd, 2019
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Symmetric properties of distributions arise in multiple settings. For each of these, separate estimators and analysis techniques have been developed. Recently, Orlitsky et al showed that a single…
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Moses Charikar Date
September 9th, 2019
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A central goal in private data analysis is to estimate statistics about an unknown distribution from a dataset possibly containing sensitive information, so that the privacy of any individual…
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Aleksandar Nikolov Date
August 19th, 2019
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We show how to solve linear programs with accuracy epsilon in time n^{omega+o(1)} log(1/epsilon) where omega~2.3728639 is the current matrix multiplication constant. This hits a natural barrier of…
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Yin Tat Lee Date
May 20th, 2019
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I
will give two lectures introducing abstract polymer models and the cluster
expansion from statistical physics. I will describe some of the original
applications of these tools in statistical…
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Will Perkins Date
May 6th, 2019
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The traveling salesman problem is one of the most fundamental optimization problems. Given n cities and pairwise distances, it is the problem of finding a tour of minimum distance that visits each…
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Ola Svensson Date
April 24th, 2019
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