Dimension reduction for regression (DRR) deals with the problem of finding for high-dimensional data such low-dimensional representations, which preserve the ability to predict a ...
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
Harold Christopher Burger, Christian J. Schuler, S...
Several marketing problems involve prediction of customer purchase behavior and forecasting future preferences. We consider predictive modeling of large scale, bi-modal or multimo...
Grid computing has become increasingly popular with the growth of the Internet, especially in large-scale scientific computation. Computational Grids are characterized by their s...
This paper addresses the problem of scheduling jobs in soft real-time systems, where the utility of completing each job decreases over time. We present a utility-based framework fo...