Abstract—In this paper, we propose a framework for employing opposition-based learning to assist evolutionary algorithms in solving discrete and combinatorial optimization proble...
—This paper describes a new method to explore and discover within a large data set. We apply techniques from preference elicitation to automatically identify data elements that a...
We show that finding small solutions to random modular linear equations is at least as hard as approximating several lattice problems in the worst case within a factor almost line...
—In this paper, we study an online bipartite matching problem, motivated by applications in wireless communication, content delivery, and job scheduling. In our problem, we have ...
Many applications in analytical domains often have the need to "connect the dots" i.e., query about the structure of data. In bioinformatics for example, it is typical t...