We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
We present a novel approach for establishing multiple-view feature correspondences along an unordered set of images taken from substantially different viewpoints. While recently s...
Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Goo...
Statistical selection procedures can identify the best of a finite set of alternatives, where “best” is defined in terms of the unknown expected value of each alternative’...
We introduce a new ensemble method based on decision tree to discover significant and diversified rules for subtype classification of childhood acute lymphoblastic leukemia, a ...
Decision-tree algorithms are known to be unstable: small variations in the training set can result in different trees and different predictions for the same validation examples. B...