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» Local Complexities for Empirical Risk Minimization
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ICRA
2003
IEEE
151views Robotics» more  ICRA 2003»
14 years 20 days ago
Adaptive real-time particle filters for robot localization
— Particle filters have recently been applied with great success to mobile robot localization. This success is mostly due to their simplicity and their ability to represent arbi...
Cody C. T. Kwok, Dieter Fox, Marina Meila
JMLR
2002
90views more  JMLR 2002»
13 years 7 months ago
Machine Learning with Data Dependent Hypothesis Classes
We extend the VC theory of statistical learning to data dependent spaces of classifiers. This theory can be viewed as a decomposition of classifier design into two components; the...
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint ...
TKDE
2010
168views more  TKDE 2010»
13 years 5 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
CORR
2010
Springer
148views Education» more  CORR 2010»
13 years 2 months ago
A Unifying View of Multiple Kernel Learning
Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different for...
Marius Kloft, Ulrich Rückert, Peter L. Bartle...
JMLR
2010
101views more  JMLR 2010»
13 years 2 months ago
Classification Using Geometric Level Sets
A variational level set method is developed for the supervised classification problem. Nonlinear classifier decision boundaries are obtained by minimizing an energy functional tha...
Kush R. Varshney, Alan S. Willsky