We present a dynamic programming approach for the solution of first-order Markov decisions processes. This technique uses an MDP whose dynamics is represented in a variant of the ...
The popular K-means clustering partitions a data set by minimizing a sum-of-squares cost function. A coordinate descend method is then used to nd local minima. In this paper we sh...
Hongyuan Zha, Xiaofeng He, Chris H. Q. Ding, Ming ...
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
Zhengzhu Feng, Richard Dearden, Nicolas Meuleau, R...
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...
We consider a control volume(covolume) method for second order elliptic PDEs with the rotated-Q1 nonconforming finite element on rectangular grids. The coefficient may a variable,...