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ECAI
2000
Springer
15 years 3 months ago
Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations
Abstract. We are interested in the relationship between learning efficiency and representation in the case of supervised neural networks for pattern classification trained by conti...
Marco Gori, Paolo Frasconi, Alessandro Sperduti
ATAL
2007
Springer
15 years 3 months ago
On discovery and learning of models with predictive representations of state for agents with continuous actions and observations
Models of agent-environment interaction that use predictive state representations (PSRs) have mainly focused on the case of discrete observations and actions. The theory of discre...
David Wingate, Satinder P. Singh
UAI
2008
15 years 1 months ago
Learning and Solving Many-Player Games through a Cluster-Based Representation
In addressing the challenge of exponential scaling with the number of agents we adopt a cluster-based representation to approximately solve asymmetric games of very many players. ...
Sevan G. Ficici, David C. Parkes, Avi Pfeffer
AAAI
2000
15 years 1 months ago
Modeling Classification and Inference Learning
Human categorization research is dominated by work in classification learning. The field may be in danger of equating the classification learning paradigm with the more general ph...
Bradley C. Love, Arthur B. Markman, Takashi Yamauc...
JMLR
2010
134views more  JMLR 2010»
14 years 6 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...