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Friday, November 24, 2017 — 3:30 PM EST

**Title:** Nash-Williams

Speaker: | Joseph Cheriyan |

Affiliation: | University of Waterloo |

Room: | MC 5501 |

**Abstract:**

Crispin Nash-Williams was one of the founding professors of C&O. The talk will cover a small sample of his mathematical work, and also his association with C&O.

Thursday, November 23, 2017 — 3:30 PM EST

**Title:** Ramsey theory for biased graphs

Speaker: | Peter Nelson |

Affiliation: | University of Waterloo |

Room: | MC 5479 |

**Abstract:**

We discuss the unavoidable subgraphs of biased graphs whose underlying graph is a clique.

Thursday, November 23, 2017 — 1:30 PM EST

**Title:** Orientations, Pseudoforests, Flows, and the Densest Subgraph

Speaker: | Markus Blumenstock |

Affiliation: | University of Mainz, Germany |

Room: | MC 6486 |

**Abstract:**

Given an undirected graph, consider the problem of finding an orientation such that the max-imum indegree is minimized. The Gabow-Westermann algorithm can solve it by exploiting the matroid structure of pseudoforests.

Wednesday, November 22, 2017 — 4:30 PM EST

**Title:** Sum-of-Squares Proofs in Optimization

Speaker: | Mehdi Karimi |

Affiliation: | University of Waterloo |

Room: | MC 5501 |

**Abstract:**

The old concept of sum-of-squares found its way into optimization and even machine learning. I will talk about this quickly evolving research area known as convex algebraic geometry.

Wednesday, November 22, 2017 — 4:00 PM EST

**Title:** Alternating Direction Method of Multipliers for the SDP Relaxation of the Quadratic Assignment Problem

Speaker: | Henry Wolkowicz |

Affiliation: | University of waterloo |

Room: | MC 5479 |

**Abstract:**

The semidefinite programming (SDP) relaxation has proven to be extremely strong for many hard discrete optimization problems. This is in particular true for the quadratic assignment problem (QAP), arguably one of the hardest NP-hard discrete optimization problems.

Friday, November 17, 2017 — 3:30 PM EST

**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.

Thursday, November 16, 2017 — 3:30 PM EST

**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.

Thursday, November 16, 2017 — 3:30 PM EST

**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.

Wednesday, November 15, 2017 — 4:00 PM EST

**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.

Friday, November 10, 2017 — 3:30 PM EST

**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.

Thursday, November 9, 2017 — 3:30 PM EST

**Title:** An Introduction to Discrete Quantum Walks

Speaker: | Harmony Zhan |

Affiliation: | University of waterloo |

Room: | MC 6486 |

**Abstract:**

Thursday, November 9, 2017 — 3:30 PM EST

**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.

Wednesday, November 8, 2017 — 4:00 PM EST

**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.

Friday, November 3, 2017 — 3:30 PM EDT

**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?

Thursday, November 2, 2017 — 3:30 PM EDT

**Title:** A short proof of a forgotten result

Speaker: | Bertrand Guenin |

Affiliation: | University of Waterloo |

Room: | MC 4042 |

**Abstract:**

Wednesday, November 1, 2017 — 4:00 PM EDT

**Title:** A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets

Speaker: | Ryan Kinnear |

Affiliation: | University of Waterloo |

Room: | MC 5479 |

**Abstract:**

We will be discussing the paper (having the same title) by Roux, Schmidt, and Bach. The authors propose a new stochastic gradient method for optimizing the sum of a finite set of smooth functions, where the sum is strongly convex.

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