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ICRA
2009
IEEE
143views Robotics» more  ICRA 2009»
14 years 4 months ago
Least absolute policy iteration for robust value function approximation
Abstract— Least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. However, it tends to be sensitive to outliers...
Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashim...
ICML
2007
IEEE
14 years 10 months ago
Robust non-linear dimensionality reduction using successive 1-dimensional Laplacian Eigenmaps
Non-linear dimensionality reduction of noisy data is a challenging problem encountered in a variety of data analysis applications. Recent results in the literature show that spect...
Samuel Gerber, Tolga Tasdizen, Ross T. Whitaker
CVPR
2010
IEEE
14 years 6 months ago
PROST: Parallel Robust Online Simple Tracking
Tracking-by-detection is increasingly popular in order to tackle the visual tracking problem. Existing adaptive methods suffer from the drifting problem, since they rely on selfup...
Jakob Santner, Christian Leistner, Amir Saffari, T...
ESANN
2003
13 years 11 months ago
Robust Topology Representing Networks
Martinetz and Schulten proposed the use of a Competitive Hebbian Learning (CHL) rule to build Topology Representing Networks. From a set of units and a data distribution, a link i...
Michaël Aupetit
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
12 years 12 days ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...