Please note: This PhD seminar will be given online.
Hong
Zhou, PhD
candidate
David
R.
Cheriton
School
of
Computer
Science
Supervisor: Professor Lap Chi Lau
In this talk, we will present a local search framework to design and analyze both combinatorial algorithms and rounding algorithms for experimental design problems. This framework provides a unifying approach to match and improve all known results in D/A/E-design and to obtain new results in previously unknown settings.
For combinatorial algorithms, we provide a new analysis of the classical Fedorov’s exchange method. We prove that this simple local search algorithm works well as long as there exists an almost optimal solution with good condition number. Moreover, we design a new combinatorial local search algorithm for E-design using the regret minimization framework.
For rounding algorithms, we provide a unified randomized exchange algorithm to match and improve previous results for D/A/E-design. Furthermore, the algorithm works in the more general setting to approximately satisfy multiple knapsack constraints, which can be used for weighted experimental design and for incorporating fairness constraints into experimental design.
Joint work with Lap Chi Lau, to appear in SODA 2021. Link to paper on ArXiv: https://arxiv.org/abs/2010.15805
To join this PhD seminar on Zoom, please go to https://zoom.us/j/98431341929?pwd=MVJ2K0dIaFVlaDh4MGxQQUpvY2dWZz09.