The paper presents a novel statistical framework for cortical folding pattern analysis that relies on a rich multivariate descriptor of folding patterns in a region of interest (RO...
Suyash P. Awate, Paul A. Yushkevich, Zhuang Song, ...
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
String kernels which compare the set of all common substrings between two given strings have recently been proposed by Vishwanathan & Smola (2004). Surprisingly, these kernels...
Generating good, production-quality plans is an essential element in transforming planners from research tools into real-world applications, but one that has been frequently overl...
A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...