The problem of nonlinear dimensionality reduction is considered. We focus on problems where prior information is available, namely, semi-supervised dimensionality reduction. It is...
Xin Yang, Haoying Fu, Hongyuan Zha, Jesse L. Barlo...
Recommender systems aim to substantially reduce information overload by suggesting lists of similar items that users may find interesting. Caching has been a useful technique for...
Umar Qasim, Vincent Oria, Yi-fang Brook Wu, Michae...
This paper deals with incremental classification and its particular application to invoice classification. An improved version of an already existant incremental neural network ca...
We propose an alternative interpretation of Bayesian surprise in the spatial domain, to account for saliency arising from contrast in image context. Our saliency formulation is in...
Ioannis Gkioulekas, Georgios Evangelopoulos, Petro...
Complex simulations can generate very large amounts of data stored disjointly across many local disks. Learning from this data can be problematic due to the difficulty of obtainin...
John Nicholas Korecki, Kevin W. Bowyer, Larry O. H...