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» The Learning Power of Evolution
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132
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ALT
2009
Springer
16 years 19 days ago
Learning from Streams
Abstract. Learning from streams is a process in which a group of learners separately obtain information about the target to be learned, but they can communicate with each other in ...
Sanjay Jain, Frank Stephan, Nan Ye
148
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LCTRTS
2007
Springer
15 years 9 months ago
Integrated CPU and l2 cache voltage scaling using machine learning
Embedded systems serve an emerging and diverse set of applications. As a result, more computational and storage capabilities are added to accommodate ever more demanding applicati...
Nevine AbouGhazaleh, Alexandre Ferreira, Cosmin Ru...
136
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JSAC
2010
138views more  JSAC 2010»
15 years 2 months ago
Dynamic conjectures in random access networks using bio-inspired learning
—Inspired by the biological entities’ ability to achieve reciprocity in the course of evolution, this paper considers a conjecture-based distributed learning approach that enab...
Yi Su, Mihaela van der Schaar
137
Voted
GLVLSI
2005
IEEE
103views VLSI» more  GLVLSI 2005»
15 years 9 months ago
Causal probabilistic input dependency learning for switching model in VLSI circuits
Switching model captures the data-driven uncertainty in logic circuits in a comprehensive probabilistic framework. Switching is a critical factor that influences dynamic, active ...
Nirmal Ramalingam, Sanjukta Bhanja
191
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ICCV
1995
IEEE
15 years 7 months ago
Geodesic Active Contours
A novel scheme for the detection of object boundaries is presented. The technique is based on active contours evolving in time according to intrinsic geometric measures of the imag...
Vicent Caselles, Ron Kimmel, Guillermo Sapiro