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...
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
There is an increasing quantity of data with uncertainty arising from applications such as sensor network measurements, record linkage, and as output of mining algorithms. This un...
Abstract. Approximation has been identified as a potential way of reducing the complexity of logical reasoning. Here we explore approximation for speeding up instance retrieval in...
The Steiner tree problem is one of the most fundamental ÆÈ-hard problems: given a weighted undirected graph and a subset of terminal nodes, find a minimum weight tree spanning ...
Jaroslaw Byrka, Fabrizio Grandoni, Thomas Rothvoss...