Contact Info
Combinatorics & Optimization
University of Waterloo
Waterloo, Ontario
Canada N2L 3G1
Phone: 519-888-4567, ext 33038
PDF files require Adobe Acrobat Reader.
Title: Robust counterpart approximations of scalar chance constraints
Speaker: | Haesol Im |
Affiliation: | University of waterloo |
Room: | MC 5479 |
Abstract:
We will cover section 2.1, section 2.2 and part of section 2.3 of the book Robust Optimization by Ben-Tal et al.
Title: The Douglas-Rachford splitting algorithm for inconsistent minimization problems
Speaker: | Walaa Moursi |
Affiliation: | Stanford University |
Room: | MC 5417 |
Abstract:
The Douglas--Rachford (DR) method is one of the most popular splitting methods in optimization. The method was first introduced in 1956 to numerically solve certain types of heat equations.
Title: Sparse graphs with forbidden induced subgraphs and the Erdos-Hajnal conjecture
Speaker: | Sophie Spirkl |
Affiliation: | Princeton University |
Room: | MC 5501 |
Abstract:
A graph G is called H-free if it does not contain H as an induced subgraph, i.e. H cannot be obtained from G by deleting vertices. A famous conjecture due to Erdos and Hajnal states that for every graph H, there is a constant c > 0 such that in every n-vertex H-free graph G, there is a set of nc vertices that are either all pairwise adjacent or all pairwise non-adjacent.
Title: Type-II Matrices
Speaker | Chris Godsil |
Affiliation: | University of Waterloo |
Room | MC 6486 |
Abstract:
The Schur product M o N of two matrices M and N is the usual entrywise product. The matrix N is the Schur inverse of M if M o N = J. Denote the Schur inverse of M by M(-). An n x n matrix is a type-II matrix if
WW(-)T = nI.
Title: Reading Seminar "Robust Optimization"
Speaker: | Group Reading |
Affiliation: | University of Waterloo |
Room: | MC 5479 |
Abstract:
In this reading seminar, we will go through Section 1. 2-1. 3 of Chapter 1 in the book 'Robust Optimization'
Title: Principled algorithms for finding local minima
Speaker: | Oliver Hinder |
Affiliation: | Stanford University |
Room: | MC 5501 |
Abstract:
Convex optimization is the cornerstone of continuous optimization, but many real problems are nonconvex: neural networks, airplane design, water network management, etc. This two part talk explores my work developing algorithms for finding local minima of nonconvex functions.
Title: Are cryptosystems based on ideal lattices quantum-safe ?
Speaker | Jean-Francois Biasse |
Affiliation: | University of South Florida |
Room: | QNC 1501 |
Abstract:
Shor's algorithm factors RSA integers and solves the Discrete Logarithm Problem (DLP) in quantum polynomial time. Therefore, alternatives to these cryptosystems must be developed to replace the current cryptographic schemes. One of the most interesting family of schemes that have been proposed for the replacement of RSA-based and DLP-based primitives relies on the hardness of finding short vectors in Euclidean lattices.
Title: Quantum Latin Squares and Magic Unitaries
Speaker: | Chris Godsil |
Affiliation: | University of Waterloo |
Room: | MC 6486 |
Abstract:
A quantum Latin square is an n x n array of vectors such that vectors in any row or any column form an orthonormal basis for Cn. A magic unitary matrix is an n x n array of projections such that each row and column sums to I.
Title: Stochastic algorithms for distributed optimization and machine learning
Speaker: | Yi Zhou |
Affiliation: | Georgia Institute of Technology |
Room: | MC 5501 |
Abstract:
In the big data era, machine learning acts as a powerful tool to transform data into knowledge that helps us make predictions and decisions. It has strong ties to the field of optimization, in the way the latter provides methods and theory.
Title: Next-generation authentication and key exchange protocols
Speaker: | Douglas Stebila |
Affiliation: | McMaster University |
Room: (change of room!) | MC 5417 |
Abstract:
Key exchange and authentication are at the heart of protocols for establishing secure communication on the Internet and other communication channels. In this talk, I'll discuss ways in which key exchange is evolving to meet new security demands and deliver new functionality.
Title: Towards Large-Scale Nonconvex/Stochastic Discrete Optimization
Speaker: | Cong Han Lim |
Affiliation: | University of Wisconsin-Madison |
Room: | MC 5501 |
Abstract:
Modern data analytics is powered by scalable mathematical optimization methods. For decision-making, we want to be able to solve large-scale mathematical problems that include discrete choices or structures. These can already be very challenging to solve exactly even when the objective and feasible region are convex.
Combinatorics & Optimization
University of Waterloo
Waterloo, Ontario
Canada N2L 3G1
Phone: 519-888-4567, ext 33038
PDF files require Adobe Acrobat Reader.
The University of Waterloo acknowledges that much of our work takes place on the traditional territory of the Neutral, Anishinaabeg and Haudenosaunee peoples. Our main campus is situated on the Haldimand Tract, the land granted to the Six Nations that includes six miles on each side of the Grand River. Our active work toward reconciliation takes place across our campuses through research, learning, teaching, and community building, and is co-ordinated within the Office of Indigenous Relations.