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» Regret Bounds for Prediction Problems
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ICCV
2003
IEEE
14 years 11 months ago
Controlling Model Complexity in Flow Estimation
This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
COLT
2006
Springer
14 years 1 months ago
Online Learning Meets Optimization in the Dual
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Shai Shalev-Shwartz, Yoram Singer
NAACL
2010
13 years 7 months ago
Distributed Training Strategies for the Structured Perceptron
Perceptron training is widely applied in the natural language processing community for learning complex structured models. Like all structured prediction learning frameworks, the ...
Ryan T. McDonald, Keith Hall, Gideon Mann
CORR
2011
Springer
205views Education» more  CORR 2011»
13 years 1 months ago
Parallel Coordinate Descent for L1-Regularized Loss Minimization
We propose Shotgun, a parallel coordinate descent algorithm for minimizing L1regularized losses. Though coordinate descent seems inherently sequential, we prove convergence bounds...
Joseph K. Bradley, Aapo Kyrola, Danny Bickson, Car...
CDC
2009
IEEE
194views Control Systems» more  CDC 2009»
14 years 1 months ago
Robust tube-based MPC for constrained mobile robots under slip conditions
— This paper focuses on the design of a robust tube-based Model Predictive Control law for the control of constrained mobile robots. A time-varying trajectory tracking error mode...
Ramon Gonzalez, Mirko Fiacchini, Jose Luis Guzman,...