The use of heuristics as a means to improve constraint solver performance has been researched widely. However, most work has been on problem-independentheuristics (e.g., variable ...
Lise Getoor, Greger Ottosson, Markus P. J. Fromher...
We propose a method of approximate dynamic programming for Markov decision processes (MDPs) using algebraic decision diagrams (ADDs). We produce near-optimal value functions and p...
The Decision Tree Learning Algorithms (DTLAs) are getting keen attention from the natural language processing research comlnunity, and there have been a series of attempts to appl...
We present multi-task structure learning for Gaussian graphical models. We discuss uniqueness and boundedness of the optimal solution of the maximization problem. A block coordina...
We present a novel discriminative training algorithm for n-gram language models for use in large vocabulary continuous speech recognition. The algorithm uses large margin estimati...