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ACCV
2007
Springer
16 years 11 days ago
Hierarchical Learning of Dominant Constellations for Object Class Recognition
Abstract. The importance of spatial configuration information for object class recognition is widely recognized. Single isolated local appearance codes are often ambiguous. On the...
Nathan Mekuz, John K. Tsotsos
ECML
1991
Springer
15 years 9 months ago
Learning by Analogical Replay in PRODIGY: First Results
Robust reasoning requires learning from problem solving episodes. Past experience must be compiled to provide adaptation to new contingencies and intelligent modification of solut...
Manuela M. Veloso, Jaime G. Carbonell
ETVC
2008
15 years 8 months ago
Intrinsic Geometries in Learning
In a seminal paper, Amari (1998) proved that learning can be made more efficient when one uses the intrinsic Riemannian structure of the algorithms' spaces of parameters to po...
Richard Nock, Frank Nielsen
AAAI
2006
15 years 7 months ago
Learning Partially Observable Action Schemas
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
Dafna Shahaf, Eyal Amir
AAAI
1992
15 years 7 months ago
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning
It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exp...
Thomas Dean, Dana Angluin, Kenneth Basye, Sean P. ...