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GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 8 months ago
Towards memoryless model building
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
David Iclanzan, Dumitru Dumitrescu
EDM
2009
147views Data Mining» more  EDM 2009»
13 years 5 months ago
Using Dirichlet priors to improve model parameter plausibility
Student modeling is a widely used approach to make inference about a student's attributes like knowledge, learning, etc. If we wish to use these models to analyze and better u...
Dovan Rai, Yue Gong, Joseph Beck
CVPR
2010
IEEE
14 years 2 months ago
Modeling and Estimating Persistent Motion with Geometric Flows
We propose a principled framework to model persistent motion in dynamic scenes. In contrast to previous efforts on object tracking and optical flow estimation that focus on local...
Dahua Lin, Eric Grimson, John Fisher
EOR
2006
104views more  EOR 2006»
13 years 7 months ago
Link function selection in stochastic multicriteria decision making models
A stochastic formulation of the Analytic Hierarchy Process (AHP) using an approach based on Bayesian categorical data models has been developed. However, in categorical data model...
Eugene D. Hahn
IROS
2007
IEEE
162views Robotics» more  IROS 2007»
14 years 2 months ago
Genetic MRF model optimization for real-time victim detection in search and rescue
— One primary goal in rescue robotics is to deploy a team of robots for coordinated victim search after a disaster. This requires robots to perform subtasks, such as victim detec...
Alexander Kleiner, Rainer Kümmerle