Abstract--Reinforcement learning (RL) research typically develops algorithms for helping an RL agent best achieve its goals-however they came to be defined--while ignoring the rela...
Kernelization algorithms are polynomial-time reductions from a problem to itself that guarantee their output to have a size not exceeding some bound. For example, d-Set Matching f...
An estimation algorithm for a query is a probabilistic algorithm that computes an approximation for the size (number of tuples) of the query. One class of estimation algorithms us...
We study the online ad-auctions problem introduced by Mehta et. al. [15]. We design a (1 − 1/e)competitive (optimal) algorithm for the problem, which is based on a clean primal-...
Semidefinite programming based approximation algorithms, such as the Goemans and Williamson approximation algorithm for the MAX CUT problem, are usually shown to have certain perf...