A new challenge in scientific computing is to merge existing simulation models to create new higher fidelity combined (often multi-level) models. While this challenge has been a...
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Abstract. Adaptation of devices and applications based on contextual information has a great potential to enhance usability and mitigate the increasing complexity of mobile devices...
Keshu Zhang, Haifeng Li, Kari Torkkola, Mike Gardn...
The deconvolution of blurred and noisy satellite images is an ill-posed inverse problem, which can be regularized within a Bayesian context by using an a priori model of the recon...
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...