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» Dynamic Modeling in Inductive Inference
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ICASSP
2011
IEEE
12 years 11 months ago
Learning and inference algorithms for partially observed structured switching vector autoregressive models
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Balakrishnan Varadarajan, Sanjeev Khudanpur
NIPS
2000
13 years 9 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick
CIARP
2007
Springer
14 years 2 months ago
Dynamic Penalty Based GA for Inducing Fuzzy Inference Systems
Abstract. Fuzzy based models have been used in many areas of research. One issue with these models is that rule bases have the potential for indiscriminant growth. Inference system...
Tomás Arredondo Vidal, Félix V&aacut...
HYBRID
2000
Springer
13 years 11 months ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
PAKDD
2000
ACM
128views Data Mining» more  PAKDD 2000»
13 years 11 months ago
Efficient Detection of Local Interactions in the Cascade Model
Detection of interactions among data items constitutes an essential part of knowledge discovery. The cascade model is a rule induction methodology using levelwise expansion of a la...
Takashi Okada