Title: Are cryptosystems based on ideal lattices quantum-safe ?
|Affiliation:||University of South Florida|
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
|Affiliation:||University of Waterloo|
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
|Affiliation:||Georgia Institute of Technology|
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
|Room: (change of room!)||MC 5417|
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|
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.