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NIPS
2003
15 years 7 months ago
Ambiguous Model Learning Made Unambiguous with 1/f Priors
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the a...
Gurinder S. Atwal, William Bialek
PRL
2008
91views more  PRL 2008»
15 years 6 months ago
Fuzzy relevance vector machine for learning from unbalanced data and noise
Handing unbalanced data and noise are two important issues in the field of machine learning. This paper proposed a complete framework of fuzzy relevance vector machine by weightin...
Dingfang Li, Wenchao Hu, Wei Xiong, Jin-Bo Yang
RIA
2006
84views more  RIA 2006»
15 years 6 months ago
Learning Recursive Automata from Positive Examples
In this theoretical paper, we compare the "classical" learning techniques used to infer regular grammars from positive examples with the ones used to infer categorial gra...
Isabelle Tellier
ALDT
2011
Springer
262views Algorithms» more  ALDT 2011»
14 years 6 months ago
Learning Complex Concepts Using Crowdsourcing: A Bayesian Approach
Abstract. We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated acc...
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton...
AAAI
1990
15 years 7 months ago
Becoming Increasingly Reactive
We describe a robot control architecture which combines a stimulus-response subsystem for rapid reaction, with a search-based planner for handling unanticipated situations. The ro...
Tom M. Mitchell