In this paper, the collision prediction between polyhedra under screw motions and a static scene using a new K dimensional tree data structure (Multiresolution Kdtree, MKtree) is ...
In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, L...
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
The Robot Intelligence Kernel (RIK) is a portable, reconfigurable suite of perceptual, behavioral, and cognitive capabilities that can be used across many different platforms, env...
David J. Bruemmer, Douglas A. Few, Miles C. Walton...
We describe and demonstrate the effectiveness of a method of predicting protein secondary structures, sheet regions in particular, using a class of stochastic tree grammars as rep...