Graphs and Matroids Seminar - Bertrand Guenin
Title: A short proof of a forgotten result
Speaker: | Bertrand Guenin |
Affiliation: | University of Waterloo |
Room: | MC 4042 |
Abstract:
Title: A short proof of a forgotten result
Speaker: | Bertrand Guenin |
Affiliation: | University of Waterloo |
Room: | MC 4042 |
Abstract:
Title: How we solve linear programs
Speaker: | Laurent Poirrier |
Affiliation: | University of Waterloo |
Room: | MC 5501 |
Abstract:
Linear programming is one of the most fundamental tools in optimization, and its theoretical complexity is well understood. In practice though, things are quite different: Which types of problems can we really solve? What sizes? With what algorithms?
Title: A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
Speaker: | Nargiz Kalantarova |
Affiliation: | University of Waterloo |
Room: | MC 5479 |
Abstract:
We will be discussing the paper (having the same title) by Amir Beck and Marc Teboulle. We consider the class of iterative shrinkage-thresholding algorithms (ISTA) for solving linear inverse problems arising in signal/image processing. This class of methods, which can be viewed as an extension of the classical gradient algorithm, is attractive due to its simplicity and thus is adequate for solving large-scale problems even with dense matrix data.
Title: An Introduction to Discrete Quantum Walks
Speaker: | Harmony Zhan |
Affiliation: | University of waterloo |
Room: | MC 6486 |
Abstract:
We will introduce the concept of a discrete quantum walk, prove some of its properties, discuss its relation to different graph structures, and construct interesting walks from these structures such as self-dual embeddings.
Title: An application of graph "recolouring”
Speaker: | Ben Moore |
Affiliation: | University of Waterloo |
Room: | MC 5479 |
Abstract:
I will prove that for any graph G, if there is an edge e such that G-e has less than (k-1)!/2 cycles of length zero mod k, then the chromatic number of G is less or equal to k.
Title: Coloring (cap even hole)-free graphs
Speaker: | Shenwei Huang |
Affiliation: | Wilfrid Laurier University |
Room: | MC 5501 |
Abstract:
An even cycle of length 4 or more is called an even hole. A cap is a cycle of length at least 5 with exactly one chord and that chord creates a triangle with the cycle. In this talk we consider (cap, even hole)-free graphs, i.e., graphs that do not contain any even hole or cap as an induced subgraph.
Title: Proximal alternating linearized minimization for nonconvex and nonsmooth problems
Speaker: | Stefan Sremac |
Affiliation: | University of Waterloo |
Room: | MC 5479 |
Abstract:
We will be discussing the paper (having the same title) by Jerome Bolte, Shoham Sabach and Marc Teboulle. We introduce a proximal alternating linearized minimization (PALM) algorithm for solving a broad class of nonconvex and nonsmooth minimization problems.
Title: Constructing cospectral graphs with a different switching
Speaker: | Chris Godsil |
Affiliation: | University of Waterloo |
Room: | MC 6486 |
Abstract:
Many years ago, Brendan McKay and I introduced a construction of pairs of cospectral graphs, sometimes known as local switching. In the same paper we introduced a second switching technique which produces, as special cases, the smallest pair of cospectral graphs and the smallest pair of connected cospectral graphs.
Title: Convex drawings of complete graphs: topology meets geometry
Speaker: | Bruce Richter |
Affiliation: | University of Waterloo |
Room: | MC 5479 |
Abstract:
A drawing D of the complete graph K(n) is the sphere is characterized by, for each isomorph J of K(5), D[J] is homeomorphic to one of the three rectilinear drawings of K(5). Every drawing of K(n) in the plane with all edges straight-line segments is obviously convex. Thus, convex drawings generalize planar point sets that are in general position.
Title: Recent Advances in Frank-Wolfe Optimization
Speaker: | Simon Lacoste-Julien |
Affiliation: | University of Montreal |
Room: | MC 5501 |
Abstract:
The Frank-Wolfe (FW) optimization algorithm has lately re-gained popularity thanks in particular to its ability to nicely handle the structured constraints appearing in machine learning and signal processing applications. However, its convergence rate is known to be slow (sublinear) when the solution lies at the boundary.