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» Dynamic Modeling in Inductive Inference
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ICML
2006
IEEE
14 years 8 months ago
Dynamic topic models
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
David M. Blei, John D. Lafferty
IMC
2006
ACM
14 years 1 months ago
Unexpected means of protocol inference
Network managers are inevitably called upon to associate network traffic with particular applications. Indeed, this operation is critical for a wide range of management functions...
Justin Ma, Kirill Levchenko, Christian Kreibich, S...
AMC
2007
80views more  AMC 2007»
13 years 8 months ago
A dynamic generating graphical model for point-sets matching
This paper presents a new dynamic generating graphical model for point-sets matching. The existing algorithms on graphical models proved to be quite robust to noise but are suscep...
Xuan Zhao, Shengjin Wang, Xiaoqing Ding
ICPR
2010
IEEE
14 years 2 months ago
Probabilistic Modeling of Dynamic Traffic Flow across Non-Overlapping Camera Views
In this paper, we propose a probabilistic method to model the dynamic traffic flow across nonoverlapping camera views. By assuming the transition time of object movement follows a...
Ching-Chun Huang, Wei-Chen Chiu, Sheng-Jyh Wang, J...
BIOCOMP
2006
13 years 9 months ago
Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
Yu Zhang, Zhidong Deng, Hongshan Jiang, Peifa Jia