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» Adapting RBF Neural Networks to Multi-Instance Learning
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ICRA
2003
IEEE
108views Robotics» more  ICRA 2003»
14 years 27 days ago
On-line safe path planning in unknown environments
s - For the on-line safe path planning of a mobile robot in unknown environments, the paper proposes a simple Hopfield Neural Network ( HNN ) planner. Without learning process, the...
Weidong Chen, Changhong Fan, Yugeng Xi
BMCBI
2010
224views more  BMCBI 2010»
13 years 7 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
NPL
2000
105views more  NPL 2000»
13 years 7 months ago
Online Interactive Neuro-evolution
In standard neuro-evolution, a population of networks is evolved in a task, and the network that best solves the task is found. This network is then fixed and used to solve future...
Adrian K. Agogino, Kenneth O. Stanley, Risto Miikk...
AAAI
2004
13 years 9 months ago
Online Parallel Boosting
This paper presents a new boosting (arcing) algorithm called POCA, Parallel Online Continuous Arcing. Unlike traditional boosting algorithms (such as Arc-x4 and Adaboost), that co...
Jesse A. Reichler, Harlan D. Harris, Michael A. Sa...
GECCO
2009
Springer
14 years 6 days ago
NEAT in increasingly non-linear control situations
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Matthias J. Linhardt, Martin V. Butz