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» Learning for Dynamic Subsumption
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NECO
2008
114views more  NECO 2008»
14 years 9 months ago
A Sparse Generative Model of V1 Simple Cells with Intrinsic Plasticity
Current models for the learning of feature detectors work on two time scales: on a fast time scale the internal neurons' activations adapt to the current stimulus; on a slow ...
Cornelius Weber, Jochen Triesch
FGCS
2007
99views more  FGCS 2007»
14 years 9 months ago
Mining performance data for metascheduling decision support in the Grid
: Metaschedulers in the Grid needs dynamic information to support their scheduling decisions. Job response time on computing resources, for instance, is such a performance metric. ...
Hui Li, David L. Groep, Lex Wolters
78
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RAS
2006
138views more  RAS 2006»
14 years 9 months ago
From pixels to multi-robot decision-making: A study in uncertainty
Mobile robots must cope with uncertainty from many sources along the path from interpreting raw sensor inputs to behavior selection to execution of the resulting primitive actions...
Peter Stone, Mohan Sridharan, Daniel Stronger, Gre...
80
Voted
TASLP
2008
158views more  TASLP 2008»
14 years 9 months ago
Score-Independent Audio Features for Description of Music Expression
Abstract--During a music performance, the musician adds expressiveness to the musical message by changing timing, dynamics, and timbre of the musical events to communicate an expre...
Luca Mion, Giovanni De Poli
INFSOF
2007
74views more  INFSOF 2007»
14 years 9 months ago
Software process improvement as emergent change: A structurational analysis
This paper presents a framework that draws on Structuration theory and dialectical hermeneutics to explicate the dynamics of software process improvement (SPI) in a packaged softw...
I. Allison, Yasmin Merali