We discuss a simple sparse linear problem that is hard to learn with any algorithm that uses a linear combination of the training instances as its weight vector. The hardness holds...
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
Matrix multiplication is an important kernel in linear algebra algorithms, and the performance of both serial and parallel implementations is highly dependent on the memory system...
Siddhartha Chatterjee, Alvin R. Lebeck, Praveen K....
This paper describes the participation of Idiap-MULTI to the Robot Vision Task at imageCLEF 2010. Our approach was based on a discriminative classification algorithm using multiple...
This paper addresses the issues of nonlinear edge-preserving image smoothing and segmentation. A ML-based approach is proposed which uses an iterative algorithm to solve the probl...