In this paper, a recurrent neural network based fuzzy inference system (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connecti...
We study online learning in an oblivious changing environment. The standard measure of regret bounds the difference between the cost of the online learner and the best decision in...
In this paper we introduce an efficient implementation of asynchronously parallel genetic algorithm with adaptive genetic operators. The classic genetic algorithm paradigm is exte...
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...