With the aim to design a general learning framework for detecting faces of various poses or under different lighting conditions, we are motivated to formulate the task as a classi...
An extension of the AdaBoost learning algorithm is proposed and brought to bear on the face detection problem. In each weak classifier selection cycle, the novel totally correctiv...
This paper presents a strategy to improve the AdaBoost algorithm with a quadratic combination of base classifiers. We observe that learning this combination is necessary to get be...
Concentration inequalities that incorporate variance information (such as Bernstein's or Bennett's inequality) are often significantly tighter than counterparts (such as...
In this work we improve top-down min-cut placers in the context of timing closure. Using the concept of boosting factors, we adjust net weights according to net spans, so as to re...