In this work we present a model that uses a Dirichlet Process (DP) with a dynamic spatial constraints to approximate a non-homogeneous hidden Markov model (NHMM). The coefficient ...
Haijun Ren, Leon N. Cooper, Liang Wu, Predrag Nesk...
We define a deterministic metric of "well-behaved data" that enables searching along the lines of interpolation search. Specifically, define to be the ratio of distance...
Recent methods based on interest points and local fingerprints have been proposed to perform robust CBCD (content-based copy detection) of images and video. They include two steps...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
This paper introduces a fast data dissemination method for structured peer-to-peer networks. The work is motivated on one side by the increase in non-volatile memory available on ...
Mihai Lupu, Jianzhong Li, Beng Chin Ooi, Shengfei ...