Dr. Jan Poland
Jan Poland, Ph.D. is Principle Scientist at Corporate Research,
His research interests include: theory of machine learning, active learning, function minimization, reinforcement learning, algorithmic information theory, decision theory, control theory, and control of complex systems.
Jan coauthored The critical spectrum of a strongly continuous semigroup, New methods for spectral clustering, Adaptive online prediction by following the perturbed leader, Prediction with expert advice by following the perturbed leader for general weights, Amplifying the block matrix structure for spectral clustering, Convergence of discrete MDL for sequential prediction, On the convergence speed of MDL predictions for Bernoulli sequences, Main vector adaptation: A CMA variant with linear time and space complexity, Defensive universal learning with experts, and Universal learning of repeated matrix games. Read the full list of his publications!
Jan earned his Ph.D. at the University of Tübingen, Germany with the thesis Modellgestützte und Evolutionäre Optimierungsverfahren für die Motorentwicklung and his Master’s at the University of Tübingen, Germany with the thesis “Der Spektrale Abbildungssatz für Operatorhalbgruppen und das Kritische Spektrum”. He did his post-doc at Lugano and Sapporo.