This paper proposes a method to optimize Viterbi beam search based on search error risk minimization in large vocabulary continuous speech recognition (LVCSR). Most speech recogni...
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...
Local search (LS) algorithms are among the most powerful techniques for solving computationally hard problems in combinatorial optimization. These algorithms could be viewed as &q...
Currently several computational problems require high processing power to handle huge amounts of data, although underlying core algorithms appear to be rather simple. Especially i...
Lars Wienbrandt, Stefan Baumgart, Jost Bissel, Car...
Top-k spatial preference queries return a ranked set of the k best data objects based on the scores of feature objects in their spatial neighborhood. Despite the wide range of loc...