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ICML
2009
IEEE
16 years 19 days ago
Proto-predictive representation of states with simple recurrent temporal-difference networks
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Takaki Makino
ICML
2008
IEEE
16 years 19 days ago
Efficiently learning linear-linear exponential family predictive representations of state
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
David Wingate, Satinder P. Singh
ICOODB
2009
94views Database» more  ICOODB 2009»
14 years 9 months ago
Metamodelling with Datalog and Classes: ConceptBase at the Age of 21
ConceptBase is a deductive object-oriented database system intended for the management of metadata. A distinguishing feature of the Telos language underlying ConceptBase is the abi...
Matthias Jarke, Manfred A. Jeusfeld, Hans W. Nisse...
HYBRID
1998
Springer
15 years 4 months ago
Large Patterns Make Great Symbols: An Example of Learning from Example
We look at distributed representation of structure with variable binding, that is natural for neural nets and allows traditional symbolic representation and processing. The repres...
Pentti Kanerva
WWW
2004
ACM
16 years 15 days ago
Ontological representation of learning objects: building interoperable vocabulary and structures
The ontological representation of learning objects is a way to deal with the interoperability and reusability of learning objects (including metadata) through providing a semantic...
Jian Qin, Naybell Hernández