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MOBISYS
2010
ACM
15 years 9 months ago
Darwin phones: the evolution of sensing and inference on mobile phones
We present Darwin, an enabling technology for mobile phone sensing that combines collaborative sensing and classification techniques to reason about human behavior and context on ...
Emiliano Miluzzo, Cory Cornelius, Ashwin Ramaswamy...
206
Voted
ECCV
2008
Springer
15 years 8 months ago
Unsupervised Classification and Part Localization by Consistency Amplification
We present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. Given a set of unlabelled images, som...
Leonid Karlinsky, Michael Dinerstein, Dan Levi, Sh...
EDM
2010
170views Data Mining» more  EDM 2010»
15 years 8 months ago
Online Curriculum Planning Behavior of Teachers
Curriculum planning is perhaps one of the most important tasks teachers must perform before instruction. While this task is facilitated by a wealth of existing online tools and res...
Keith E. Maull, Manuel Gerardo Saldivar, Tamara Su...
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
15 years 6 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
BMCBI
2008
138views more  BMCBI 2008»
15 years 6 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones
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