Learning in Compositional Hierarchies: Inducing the Structure of Objects from Data Export

@inproceedings{citeulike:2529059, abstract = {I propose a learning algorithm for learning hierarchical models for object recognition. The model architecture is a compositional hierarchy that represents part-whole relationships: parts are described in the local context of substructures of the object. The focus of this report is learning hierarchical models from data, i.e. inducing the structure of model prototypes from observed exemplars of an object. At each node in the hierarchy, a probability distribution governing its parameters must be ...}, author = {Utans, Joachim}, booktitle = {Advances in Neural Information Processing Systems}, citeulike-article-id = {2529059}, citeulike-linkout-0 = {http://citeseer.ist.psu.edu/utans94learning.html}, citeulike-linkout-1 = {http://citeseer.lcs.mit.edu/utans94learning.html}, citeulike-linkout-2 = {http://citeseer.ifi.unizh.ch/utans94learning.html}, citeulike-linkout-3 = {http://citeseer.comp.nus.edu.sg/utans94learning.html}, editor = {Cowan, Jack D. and Tesauro, Gerald and Alspector, Joshua}, keywords = {laeyer}, pages = {285--292}, posted-at = {2008-03-13 17:55:51}, priority = {2}, publisher = {Morgan Kaufmann Publishers, Inc.}, title = {Learning in Compositional Hierarchies: Inducing the Structure of Objects from Data}, url = {http://citeseer.ist.psu.edu/utans94learning.html}, volume = {6}, year = {1994} }

TY - CONF ID - citeulike:2529059 L3 - citeulike-article-id:2529059 N2 - I propose a learning algorithm for learning hierarchical models for object recognition. The model architecture is a compositional hierarchy that represents part-whole relationships: parts are described in the local context of substructures of the object. The focus of this report is learning hierarchical models from data, i.e. inducing the structure of model prototypes from observed exemplars of an object. At each node in the hierarchy, a probability distribution governing its parameters must be ... EP - 292 TI - Learning in Compositional Hierarchies: Inducing the Structure of Objects from Data PB - Morgan Kaufmann Publishers, Inc. VL - 6 T2 - Advances in Neural Information Processing Systems SP - 285 KW - laeyer AU - Utans, Joachim A2 - Cowan, Jack A2 - Tesauro, Gerald A2 - Alspector, Joshua PY - 1994/// UR - http://citeseer.ist.psu.edu/utans94learning.html ER -