Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Abstract. We study the approximation of the integration of multivariate functions classes in the quantum model of computation. We first obtain a lower bound of the n-th minimal qu...
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
Efficient matching of incoming events to persistent queries is fundamental to event pattern matching, complex event processing, and publish/subscribe systems. Recent processing e...
Lars Brenna, Johannes Gehrke, Mingsheng Hong, Dag ...
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...