We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
Ranking large scale image and video collections usually expects higher accuracy on top ranked data, while tolerates lower accuracy on bottom ranked ones. In view of this, we propo...
Inspired by Darwinian evolution, a genetic algorithm (GA) approach is one of the popular heuristic methods for solving hard problems, such as the Job Shop Scheduling Problem (JSSP...
Pointer analyses derived from a Context-Free-Language (CFL) reachability formulation achieve very high precision, but they do not scale well to compute the points-to solution for a...
Capacity scaling is a hierarchical approach to graph representation that can improve theoretical complexity and practical efficiency of max-flow/min-cut algorithms. Introduced by ...