In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
This paper proposes a novel method for blindly separating unobservable independent component (IC) signals based on the use of a genetic algorithm. It is intended for its applicati...
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
We present a new, statistical approach to rule learning. Doing so, we address two of the problems inherent in traditional rule learning: The computational hardness of finding rule...
This paper introduces a new algorithm, namely the EquiCorrelation Network (ECON), to perform supervised classification, and regression. ECON is a kernelized LARS-like algorithm, b...
Manuel Loth, Philippe Preux, Samuel Delepoulle, Ch...