When selecting alternatives from large amounts of data, trade-offs play a vital role in everyday decision making. In databases this is primarily reflected by the top-k retrieval p...
Advances in the development of large scale distributed computing systems such as Grids and Computing Clouds have intensified the need for developing scheduling algorithms capable...
Claris Castillo, George N. Rouskas, Khaled Harfous...
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
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...
It has long been recognized that capturing term relationships is an important aspect of information retrieval. Even with large amounts of data, we usually only have significant ev...