In this work we extend the work of Dean, Kaelbling, Kirman and Nicholson on planning under time constraints in stochastic domains to handle more complicated scheduling problems. I...
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
In this paper, we present an ant system algorithm variant designed to solve the job shop scheduling problem. The proposed approach is based on a recent biological study which showe...
Modern use of FPGAs as hardware accelerators involves the partial reconfiguration of hardware resources as the application executes. In this paper, we present a polynomial time al...
Extensible processors allow addition of application-specific custom instructions to the core instruction set architecture. However, it is computationally expensive to automaticall...