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» Local Probabilistic Models for Link Prediction
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CVPR
2009
IEEE
15 years 2 months ago
Observe Locally, Infer Globally: a Space-Time MRF for Detecting Abnormal Activities with Incremental Updates
We propose a space-time Markov Random Field (MRF) model to detect abnormal activities in video. The nodes in the MRF graph correspond to a grid of local regions in the video fra...
Jaechul Kim (University of Texas at Austin), Krist...
ICIP
2007
IEEE
14 years 1 months ago
Key-Places Detection and Clustering in Movies Using Latent Aspects
We describe a new method to find and cluster recurrent keyplaces in a movie. It consists of an unsupervised classification of shots that are taking place in the same physical loca...
Maguelonne Héritier, Samuel Foucher, Langis...
INFOCOM
2005
IEEE
14 years 1 months ago
Modelling and stability of FAST TCP
We discuss the modelling of FAST TCP and prove four stability results. Using the traditional continuous-time flow model, we prove, for general networks, that FAST TCP is globally ...
Jiantao Wang, David X. Wei, Steven H. Low
IJCAI
2007
13 years 9 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans
BMCBI
2005
89views more  BMCBI 2005»
13 years 7 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg