Image Based Rendering holds a lot of promise for navigating through a real world scene without modeling it manually. Different representations have been proposed for IBR in the li...
P. J. Narayanan, Sashi Kumar Penta, Sireesh Reddy ...
We propose a probabilistic, generative account of configural learning phenomena in classical conditioning. Configural learning experiments probe how animals discriminate and gener...
Aaron C. Courville, Nathaniel D. Daw, David S. Tou...
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
We propose a directed graphical representation of utility functions, called UCP-networks, that combines aspects of two existing preference models: generalized additive models and ...
The labor intensive aspects of simulation development and maintenance make exploration of reuse essential. However, reuse is generally difficult to achieve in practice due to infl...
Joseph C. Carnahan, Paul F. Reynolds Jr., David C....