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» Managing Complexity in Large Learning Robotic Systems
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CTW
2002
74views more  CTW 2002»
13 years 7 months ago
Nine Steps to Move Forward from Error
: Following celebrated failures stakeholders begin to ask questions about how to improve the systems and processes they operate, manage or depend on. In this process it is easy to ...
David D. Woods, Richard I. Cook
BMCBI
2008
166views more  BMCBI 2008»
13 years 8 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf
CACM
2010
161views more  CACM 2010»
13 years 6 months ago
Efficiently searching for similar images
As it becomes increasingly viable to capture, store, and share large amounts of image and video data, automatic image analysis is crucial to managing visual information. Many prob...
Kristen Grauman
DAGSTUHL
2009
13 years 9 months ago
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Erzsébet Merényi, Kadim Tasdemir, Li...
DEXAW
2003
IEEE
122views Database» more  DEXAW 2003»
14 years 1 months ago
A Framework for Self-Optimizing Grids Using P2P Components
We present the framework of a new grid architecture based on the peer-to-peer and the component paradigms. In our architecture, several peer-to-peer components are loosely coupled...
Florian Schintke, Thorsten Schütt, Alexander ...