Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Adaptive Operator Selection (AOS) turns the impacts of the applications of variation operators into Operator Selection through a Credit Assignment mechanism. However, most Credit ...
Detection of visually salient image regions is useful for applications like object segmentation, adaptive compression, and object recognition. Recently, full-resolution salient ma...
In this paper we study the problem of classifying chemical compound datasets. We present a sub-structure-based classification algorithm that decouples the sub-structure discovery...
Mukund Deshpande, Michihiro Kuramochi, George Kary...