Feature selection is fundamental to knowledge discovery from massive amount of high-dimensional data. In an effort to establish theoretical justification for feature selection al...
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
Because of the high volume and unpredictable arrival rate, stream processing systems may not always be able to keep up with the input data streams-- resulting in buffer overflow a...
In this paper, we propose a conceptual framework for developing a family of models for Group-Centric information sharing. The traditional approach to information sharing, characte...
Ram Krishnan, Ravi S. Sandhu, Jianwei Niu, William...
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...