In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
The total variation model of Rudin, Osher, and Fatemi for image denoising is considered to be one of the best denoising models. In the past, its solutions were based on nonlinear ...
This paper presents a predictable and grouped genetic algorithm (PGGA) for job scheduling. The novelty of the PGGA is twofold: (1) a job workload estimati...
We present an efficient algorithm for solving the ray-shooting problem on high dimensional sets. Our algorithm computes the intersection of the boundary of a compact convex set w...
We model budget-constrained keyword bidding in sponsored search auctions as a stochastic multiple-choice knapsack problem (S-MCKP) and design an algorithm to solve S-MCKP and the ...