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...
—As wireless power charging technology emerges, some basic principles in sensor network design are changed accordingly. Existing sensor node deployment and data routing strategie...
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
When an evolutionary algorithm addresses a sequence of instances of the same problem, it can seed its population with solutions that it found for previous instances. This techniqu...
Metaheuristics have often been shown to be effective for difficult combinatorial optimization problems. The reason for that, however, remains unclear. A framework for a theory of ...