Although a deterministic polytime algorithm for primality testing is now known ([4]), the Rabin-Miller randomized test of primality continues being the most efficient and widely u...
We present a new heuristic approach for maximal constraint satisfaction of overconstrained problems (MAX-CSP). This approach is based on a formulation of CSP as an optimization pro...
In this paper, we propose a new feature selection criterion. It is based on the projections of data set elements onto each attribute. The main advantages are its speed and simplici...
An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data needs to be used repea...
Universal kernels have been shown to play an important role in the achievability of the Bayes risk by many kernel-based algorithms that include binary classification, regression, ...
Bharath K. Sriperumbudur, Kenji Fukumizu, Gert R. ...