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CVPR
1999
IEEE
16 years 6 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
ESAS
2006
Springer
15 years 8 months ago
Dynamics of Learning Algorithms for the On-Demand Secure Byzantine Routing Protocol
We investigate the performance of of several protocol enhancements to the On-Demand Secure Byzantine Routing (ODSBR) [3] protocol in the presence of various Byzantine Attack models...
Baruch Awerbuch, Robert G. Cole, Reza Curtmola, Da...
KES
2004
Springer
15 years 9 months ago
An Objective Function Based on Fuzzy Preferences in Dynamic Decision Making
Abstract. This paper presents a mathematical model for dynamic decision making with an objective function induced from fuzzy preferences. The fuzzy preference is related to decisio...
Yuji Yoshida, Masami Yasuda, Jun-ichi Nakagami, Ma...
ATAL
2008
Springer
15 years 6 months ago
Switching dynamics of multi-agent learning
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
Peter Vrancx, Karl Tuyls, Ronald L. Westra
CVPR
2010
IEEE
16 years 19 days ago
Clustering Dynamic Textures with the Hierarchical EM Algorithm
The dynamic texture (DT) is a probabilistic generative model, defined over space and time, that represents a video as the output of a linear dynamical system (LDS). The DT model ...
Antoni Chan, Emanuele Coviello, Gert Lanckriet