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» Object correspondence as a machine learning problem
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JMLR
2010
169views more  JMLR 2010»
14 years 8 months ago
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
106
Voted
ICMLC
2010
Springer
15 years 12 days ago
An integrity-based fuzzy c-means method resolving cluster size sensitivity problem
: Cluster size insensitive FCM (csiFCM) dynamically adjusts the membership value of each object based on the size of the cluster to which it is assigned after defuzzification to re...
Y. H. Lai, P. W. Huang, P. L. Lin
125
Voted
COLT
2006
Springer
15 years 5 months ago
Online Learning with Constraints
In this paper, we study a sequential decision making problem. The objective is to maximize the total reward while satisfying constraints, which are defined at every time step. The...
Shie Mannor, John N. Tsitsiklis
ICALT
2007
IEEE
15 years 8 months ago
Adapting health care competencies to a formal competency model
Health professions education has moved away from process-based curricula to competency-based curricula. Machine readable and processable health care competencies are still embryon...
Onjira Sitthisak, Lester Gilbert, Hugh C. Davis, M...
CVPR
2004
IEEE
16 years 3 months ago
Is Bottom-Up Attention Useful for Object Recognition?
A key problem in learning multiple objects from unlabeled images is that it is a priori impossible to tell which part of the image corresponds to each individual object, and which...
Ueli Rutishauser, Dirk Walther, Christof Koch, Pie...