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ICML
2008
IEEE
16 years 4 months ago
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
COLT
2000
Springer
15 years 7 months ago
PAC Analogues of Perceptron and Winnow via Boosting the Margin
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
Rocco A. Servedio
161
Voted
CORR
2011
Springer
189views Education» more  CORR 2011»
14 years 10 months ago
Analysis of multi-stage open shop processing systems
We study algorithmic problems in multi-stage open shop processing systems that are centered around reachability and deadlock detection questions. We characterize safe and unsafe s...
Christian Eggermont, Alexander Schrijver, Gerhard ...
141
Voted
COLT
2003
Springer
15 years 8 months ago
Lower Bounds on the Sample Complexity of Exploration in the Multi-armed Bandit Problem
We consider the Multi-armed bandit problem under the PAC (“probably approximately correct”) model. It was shown by Even-Dar et al. [5] that given n arms, it suffices to play th...
Shie Mannor, John N. Tsitsiklis
128
Voted
COMPGEOM
1996
ACM
15 years 7 months ago
Linear Complexity Hexahedral Mesh Generation
We show that any simply connected (but not necessarily convex) polyhedron with an even number of quadrilateral sides can be partitioned into O(n) topological cubes, meeting face t...
David Eppstein