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» Evaluating the Robustness of Learning from Implicit Feedback
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ER
2006
Springer
112views Database» more  ER 2006»
15 years 3 months ago
An Architecture for Emergent Semantics
Emergent Semantics is a new paradigm for inferring semantic meaning from implicit feedback by a sufficiently large number of users of an object retrieval system. In this paper, we ...
Sven Herschel, Ralf Heese, Jens Bleiholder
CHI
2010
ACM
15 years 6 months ago
Examining multiple potential models in end-user interactive concept learning
End-user interactive concept learning is a technique for interacting with large unstructured datasets, requiring insights from both human-computer interaction and machine learning...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
IEAAIE
2005
Springer
15 years 5 months ago
Movement Prediction from Real-World Images Using a Liquid State Machine
Prediction is an important task in robot motor control where it is used to gain feedback for a controller. With such a self-generated feedback, which is available before sensor rea...
Harald Burgsteiner, Mark Kröll, Alexander Leo...
BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
15 years 3 months ago
Learning Scaling Coefficient in Possibilistic Latent Variable Algorithm from Complex Diagnosis Data
—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...
Zong-Xian Yin
ICML
2000
IEEE
16 years 16 days ago
Eligibility Traces for Off-Policy Policy Evaluation
Eligibility traces have been shown to speed reinforcement learning, to make it more robust to hidden states, and to provide a link between Monte Carlo and temporal-difference meth...
Doina Precup, Richard S. Sutton, Satinder P. Singh