The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
We present a framework for visualizing remote distributed data sources using a multi-user immersive virtual reality environment. DIVE-ON is a system prototype that consolidates dis...
Data integration has evolved to provide efficient data management across distributed and heterogeneous data sources in grid environment. However, existing works in data integratio...
Yongwei Wu, Jia Liu, Gang Chen, Guangwen Yang, Bo ...
We present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. O...