We have been using the concept map of the domain, enhanced with pedagogical concepts called learning objectives, as the overlay student model in our intelligent tutors for program...
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
nd: A key abstraction in representing proteomics knowledge is the notion of unique identifiers for individual entities (e.g. proteins) and the massive graph of relationships among...
Andrew K. Smith, Kei-Hoi Cheung, Kevin Y. Yip, Mar...
This paper presents a hierarchical-compositional model of human faces, as a three-layer AND-OR graph to account for the structural variabilities over multiple resolutions. In the A...
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...