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» A Framework for Multiple-Instance Learning
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ECML
2001
Springer
14 years 10 days ago
Comparing the Bayes and Typicalness Frameworks
When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If the prior is incorrect however, these...
Thomas Melluish, Craig Saunders, Ilia Nouretdinov,...
HICSS
2008
IEEE
151views Biometrics» more  HICSS 2008»
14 years 2 months ago
A Conceptual Framework of Transactive Networks System
A virtual organization is a temporary network of companies, which implies the potential opportunity to learn and share abundant sources of complementary and compatible knowledge p...
Sheng-cheng Lin, Yu-Min Wang, Daniel Y. Shee
ICML
2005
IEEE
14 years 8 months ago
Hedged learning: regret-minimization with learning experts
In non-cooperative multi-agent situations, there cannot exist a globally optimal, yet opponent-independent learning algorithm. Regret-minimization over a set of strategies optimiz...
Yu-Han Chang, Leslie Pack Kaelbling
IJCAI
2007
13 years 9 months ago
Deictic Option Schemas
Deictic representation is a representational paradigm, based on selective attention and pointers, that allows an agent to learn and reason about rich complex environments. In this...
Balaraman Ravindran, Andrew G. Barto, Vimal Mathew
ICALT
2007
IEEE
14 years 2 months ago
PALS2: Pedagogically Adaptive Learning System based on Learning Styles
One of the most contemporary research ideas for adaptive web-based educational systems is personalizing the educational contents, based on users’ learning styles. Moreover, it i...
Melody Siadaty, Fattaneh Taghiyareh