Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
Object detection and recognition has achieved a significant progress in recent years. However robust 3D object detection and segmentation in noisy 3D data volumes remains a challen...
Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang...
Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...