Algebraic Complexity Theory is a field in which one studies complexity theoretic questions surrounding algebraic objects. In this talk we will be broadly discussing two such problems.
We show EOPL=PLS PPAD. Here the class EOPL consists of all total search problems that reduce to the End-of-Potential-Line problem, which was introduced in the works by Hubacek and Yogev (SICOMP 2020) and Fearnley et al. (JCSS 2020).
Reconfiguring a system (generally represented by a graph) means gradually transforming one configuration of the system to another configuration by modifying it in a slow and steady step-by-step manner.
One of the fundamental components of quantum theory is measurement. one can think of measurement as the interface between the quantum world and our everyday world.
It is well known that the classic Los-Tarski preservation theorem fails in the finite: there are first order definable classes of finite structures closed under extensions which are not definable in the existential fragment of first order logic.
We will see how Fano's inequality, a classical result from information theory, can be used to get tight lower bounds on sample complexity of various learning problems.
Differential privacy (DP) gives a rigorous framework for data privacy by giving guarantees on the information leakage for individual data points from the output of an algorithm.
We study information transmission over quantum channels in the one shot setting. We primarily consider multiterminal channels and develop several tools to send quantum information over these channels.