# Past Events

# Randomized Communication Complexity of Set Disjointness

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In this talk we will study the communication complexity of the disjointness function, in which each of two players holds a $k$-subset of a universe of size $n$ and the goal is to determine whether the sets are disjoint.

# Static vs Adjustable Solutions in Dynamic Optimization

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We study the performance of static solutions for two-stage adjustable robust linear optimization problems with uncertain constraint and objective coefficients and give a tight characterization of the adaptivity gap.

# A Johnson-Lindenstrauss Lemma With Independent Subgaussian Projection Coefficients

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The Johnson-Lindenstrauss lemma asserts that any n-point set in any Euclidean space can be mapped to a Euclidean space of dimension $k= O(\epsilon^{-2} \log n)$ so that all distances are preserved upto a multiplicative factor between $(1 - \epsilo

# A Markov Chain Approximation for Choice Modeling

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# A Statistical View to Boosting

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In machine learning, AdaBoost has been an extremely popular boosting algorithm to improve the performance of ``weak learners". AdaBoost was initially proposed by Schapire and Freund from an algorithmic perspective.

# Fundamental Limits on Communication Energy Via "Information-friction"

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Just as there are frictional losses in moving a weight on a surface, there are also frictional losses in moving information on a substrate.

# Complex Online Decision Making

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Suppose you want to find the least congested route in an ad hoc network. Each link's rate is unknown and stochastic, and each time you get to see the minimum rate (i.e., bottleneck) along any route you pick.

# Some Mathematical Problems Arising in the Study of Chemical Reaction Networks

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Networks of chemical reactions have natural underlying combinatorial structure, allowing them to be represented as graphs or digraphs, perhaps with additional vertex or edge colourings/labellings.