—Multistage stochastic programs are effective for solving long-term planning problems under uncertainty. Such programs are usually based on scenario generation model about future...
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
Kai Ni, John William Paisley, Lawrence Carin, Davi...
Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach t...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor
Background estimation and removal based on the joint use of range and color data produces superior results than can be achieved with either data source alone. This is increasingly...
Gaile G. Gordon, Trevor Darrell, Michael Harville,...
Conventional research on similarity search focuses on measuring the similarity between objects with the same type. However, in many real-world applications, we need to measure the...
Chuan Shi, Xiangnan Kong, Philip S. Yu, Sihong Xie...