Kernel approximation is commonly used to scale kernel-based algorithms to applications containing as many as several million instances. This paper analyzes the effect of such appr...
This paper describes a technique for evolving similar solutions to similar configuration design problems. Using the configuration design of combination logic circuits as a testb...
The goal of our current research is machine learning with the help and guidance of a knowledge base (KB). Rather than learning numerical models, our approach generates explicit sy...
Incorporating invariances into a learning algorithm is a common problem in machine learning. We provide a convex formulation which can deal with arbitrary loss functions and arbit...
Choon Hui Teo, Amir Globerson, Sam T. Roweis, Alex...
Algorithmic composition of musical pieces is one of the most popular areas of computer aided music research. Various attempts have been made successfully in the area of music comp...