We propose a novel and robust model to represent and learn generic 3D object categories. We aim to solve the problem of true 3D object categorization for handling arbitrary rotati...
In this paper, we present a robust method for estimating the model parameters in a mixture of probabilistic principal component analyzers. This method is based on the Stochastic v...
While several hierarchical classification methods have been applied to web content, such techniques invariably rely on a pre-defined taxonomy of documents. We propose a new techni...
In this paper, we will examine the frequent pattern mining for uncertain data sets. We will show how the broad classes of algorithms can be extended to the uncertain data setting....
Charu C. Aggarwal, Yan Li, Jianyong Wang, Jing Wan...
Not all operating systems are created equal. Contrasting traditional monolithic kernels, there is a class of systems called microkernels more prevalent in embedded systems like ce...