Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
We consider the problem of constructing decision trees for entity identification from a given relational table. The input is a table containing information about a set of entities...
Venkatesan T. Chakaravarthy, Vinayaka Pandit, Samb...
We present approximation and online algorithms for a number of problems of pricing items for sale so as to maximize seller’s revenue in an unlimited supply setting. Our first r...
The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
Information extraction is one of the most important techniques used in Text Mining. One of the main problems in building information extraction (IE) systems is that the knowledge ...