We study the online version of the classical parallel machine scheduling problem to minimize the total weighted completion time from the perspective of algorithmic mechanism desig...
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Support vector machines (SVMs) have been widely used in multimedia retrieval to learn a concept in order to find the best matches. In such a SVM active learning environment, the ...
The main idea of iceberg data cubing methods relies on optimization techniques for computing only the cuboids cells above certain minimum support threshold. Even using such approac...
Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit ...