We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Decentralized partially observable Markov decision process (DEC-POMDP) is an approach to model multi-robot decision making problems under uncertainty. Since it is NEXP-complete the...
We propose a method of using shape adaptation for compression of light fields of 3-D objects. Shape adaptation is incorporated into two light field coders, both applying disparity...
Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of selecting k skyline points so that the number of points,...
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...