Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Motivated by the problem of customer wallet estimation, we propose a new setting for multi-view regression, where we learn a completely unobserved target (in our case, customer wa...
We consider the problem of selecting a subset of m most informative features where m is the number of required features. This feature selection problem is essentially a combinator...
Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, ...
Abstract. We consider the question of protecting the privacy of customers buying digital goods. More specifically, our goal is to allow a buyer to purchase digital goods from a ve...