In this paper we present efficient deterministic and randomized algorithms for selection on any interconnection network when the number of input keys (n) is the number of processo...
Sequential Minimal Optimization (SMO) is currently the most popular algorithm to solve large quadratic programs for Support Vector Machine (SVM) training. For many variants of this...
In this letter, a two-step learning scheme for the optimal selection of time lags is proposed for a typical temporal blind source separation (TBSS), Temporal Decorrelation source ...
Zhan-Li Sun, De-Shuang Huang, Chun-Hou Zheng, Li S...
One major problem of existing methods to mine data streams is that it makes ad hoc choices to combine most recent data with some amount of old data to search the new hypothesis. T...
The family of threshold algorithm (i.e., TA) has been widely studied for efficiently computing top-k queries. TA uses a sort-merge framework that assumes data lists are pre-sorted...