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SERVICES
2008
71views more  SERVICES 2008»
15 years 4 months ago
Using Problems to Learn Service-Oriented Computing
Service-oriented computing and the ensuing science of services represent significant challenges to academia. As we come to grips with its many implications, we are slowly beginnin...
Sandeep Purao, Vijay K. Vaishnavi, John W. Bagby, ...
134
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ICVGIP
2004
15 years 4 months ago
On Learning Shapes from Shades
Shape from Shading (SFS) is one of the most extensively studied problems in Computer Vision. However, most of the approaches only deal with Lambertian or other specific shading mo...
Subhajit Sanyal, Mayank Bansal, Subhashis Banerjee...
96
Voted
IJCAI
1993
15 years 3 months ago
Evolutionary Learning Strategy using Bug-Based Search
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
123
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DA
2010
123views more  DA 2010»
14 years 11 months ago
Paradoxes in Learning and the Marginal Value of Information
We consider the Bayesian ranking and selection problem, in which one wishes to allocate an information collection budget as efficiently as possible to choose the best among severa...
Peter Frazier, Warren B. Powell
128
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ICML
2010
IEEE
15 years 3 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...