Structured outputs such as multidimensional vectors or graphs are frequently encountered in real world pattern recognition applications such as computer vision, natural language pr...
In this paper, we model large support vector machines (SVMs) by smaller networks in order to decrease the computational cost. The key idea is to generate additional training patte...
Pramod Lakshmi Narasimha, Sanjeev S. Malalur, Mich...
We propose machine learning methods for the estimation of deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspo...
We study hierarchical classification in the general case when an instance could belong to more than one class node in the underlying taxonomy. Experiments done in previous work sh...
We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection metho...