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ALT
2002
Springer
14 years 4 months ago
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Dmitry Gavinsky
ICRA
2008
IEEE
155views Robotics» more  ICRA 2008»
14 years 2 months ago
Learning tactic-based motion models with fast particle smoothing
— Learning parameters of a motion model is an important challenge for autonomous robots. We address the particular instance of parameter learning when tracking motions with a swi...
Yang Gu, Manuela M. Veloso
CVPR
2004
IEEE
14 years 9 months ago
Local Smoothing for Manifold Learning
We propose methods for outlier handling and noise reduction using weighted local linear smoothing for a set of noisy points sampled from a nonlinear manifold. The methods can be u...
Jin Hyeong Park, Zhenyue Zhang, Hongyuan Zha, Rang...
GRC
2008
IEEE
13 years 8 months ago
Neighborhood Smoothing Embedding for Noisy Manifold Learning
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
Guisheng Chen, Junsong Yin, Deyi Li
CORR
2012
Springer
232views Education» more  CORR 2012»
12 years 3 months ago
Smoothing Proximal Gradient Method for General Structured Sparse Learning
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbone...