Maximum a posteriori (MAP) inference in Markov Random Fields (MRFs) is an NP-hard problem, and thus research has focussed on either finding efficiently solvable subclasses (e.g. t...
Dhruv Batra, Andrew Gallagher, Devi Parikh, Tsuhan...
To handle problems created by large data sets, we propose a method that uses a decision tree to decompose a given data space and train SVMs on the decomposed regions. Although the...
Fu Chang, Chien-Yang Guo, Xiao-Rong Lin, Chi-Jen L...
Caenorhabditis elegans is an important model organism for the study of molecular mechanisms of development and disease processes, due to its well-known genome and invariant cell l...
This paper presents an extensive study about the evolution of textual content on the Web, which shows how some new pages are created from scratch while others are created using al...
This paper presents KnowledgeTree, an architecture for adaptive E-Learning based on distributed reusable intelligent learning activities. The goal of KnowledgeTree is to bridge th...