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» Using Machine Learning to Focus Iterative Optimization
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85
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COLT
2006
Springer
15 years 6 months ago
Optimal Oracle Inequality for Aggregation of Classifiers Under Low Noise Condition
We consider the problem of optimality, in a minimax sense, and adaptivity to the margin and to regularity in binary classification. We prove an oracle inequality, under the margin ...
Guillaume Lecué
133
Voted
JMLR
2010
187views more  JMLR 2010»
14 years 9 months ago
SFO: A Toolbox for Submodular Function Optimization
In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
Andreas Krause
135
Voted
ICML
2009
IEEE
16 years 3 months ago
More generality in efficient multiple kernel learning
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
Manik Varma, Bodla Rakesh Babu
CRV
2009
IEEE
115views Robotics» more  CRV 2009»
15 years 9 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
121
Voted
ICML
2006
IEEE
16 years 3 months ago
Maximum margin planning
Mobile robots often rely upon systems that render sensor data and perceptual features into costs that can be used in a planner. The behavior that a designer wishes the planner to ...
Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinke...