Current students

Title: The upper density of monochromatic infinite paths

Abstract: Given a complete graph $K_n$, whose edges are coloured in red and blue, what is the longest monochromatic path one can find?

Title: Implementing supersingular isogeny cryptography

Abstract:

Recent years have seen dramatic progress and improvements in the implementation of supersingular isogeny-based cryptosystems.

Title:  A Short Proof of the Containers Theorem for Hypergraphs

Abstract:  A modern trend in extremal combinatorics is extending classical results from the dense setting (e.g. Szemerédi's theorem)

Title: Stability Yields a PTAS for k-Median and k-Means Clustering

Abstract: Previously, we have seen a variety of approximation methods for k-median, and last week we saw

Title: Why Random Reshuffling Beats Stochastic Gradient Descent

Abstract:  Over the first few lectures in the seminar we studied the Stochastic Gradient Descent (SGD) method

The "blood, sweat, tears, toil and triumphs" of commercializing technology

Marc Morin is the co-founder and CEO of Auvik Networks, creators of cloud-based software that makes it dramatically easier for IT managed service providers to monitor and manage their clients' IT networks. A serial entrepreneur, Marc has previously co-founded several successful companies, including PixStream (acquired by Cisco for USD$369 million) and Sandvine (Sold to Francisco Partners for CAD$582 million), and is a seed investor in a number of local tech companies.

Title: Solving DNN Relaxations of the Quadratic Assignment Problem with ADMM and Facial Reduction

Abstract:

The quadratic assignment problem, QAP, has many important applications ranging from the planning of building locations of a university, to the positioning of modules on a computer chip (VLSI design), to the design of keyboards.

Title: Approximation Algorithms for Distributionally Robust Stochastic Optimization

Abstract:

Two-stage stochastic optimization is a widely-used framework for modeling uncertainty, where we have a probability distribution over possible realizations of the data, called scenarios, and decisions are taken in two stages: we make first-stage decisions knowing only the underlying distribution and before a scenario is realized, and may take additional second-stage recourse actions after a scenario is realized.

Title: Approximate Clustering without the Approximation

Abstract: Previously in this CombOpt Reading Group series, we have discussed improving approximation factors for particular distance-based objective functions in clustering problems.

Title:  2-universality of random graphs.

Abstract: For a family of graphs F, a graph G is F-universal if G contains every graph in F as a (not necessarily induced) subgraph.