Genetic programming is known to be capable of creating designs that satisfy prespecified high-level design requirements for analog electrical circuits and other complex structures...
John R. Koza, Forrest H. Bennett III, Oscar Stiffe...
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...
The paper presents a compiler framework for analyzing and optimizing OpenMP programs. The framework includes Parallel Control Flow Graph and Parallel Data Flow equations based on t...
We present a new method to compute upper bounds of the number of solutions of binary integer programming (BIP) problems. Given a BIP, we create a dynamic programming (DP) table for...
Siddhartha Jain, Serdar Kadioglu, Meinolf Sellmann
We formulate the problem of nonprojective dependency parsing as a polynomial-sized integer linear program. Our formulation is able to handle non-local output features in an effici...