We propose XSEED, a synopsis of path queries for cardinality estimation that is accurate, robust, efficient, and adaptive to memory budgets. XSEED starts from a very small kernel,...
Data mining applications analyze large collections of set data and high dimensional categorical data. Search on these data types is not restricted to the classic problems of minin...
We address the problem of automatic object classification for traffic scene surveillance, which is very challenging for the low resolution videos, large intraclass variations and ...
Many computer vision algorithms make use of local features, and rely on a systematic comparison of these features. The chosen dissimilarity measure is of crucial importance for th...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...