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ISNN
2007
Springer
16 years 1 months ago
A Hierarchical Self-organizing Associative Memory for Machine Learning
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
Janusz A. Starzyk, Haibo He, Yue Li
SGAI
2007
Springer
16 years 1 months ago
Learning Sets of Sub-Models for Spatio-Temporal Prediction
In this paper we describe a novel technique which implements a spatiotemporal model as a set of sub-models based on first order logic. These sub-models model different, typicall...
Andrew Bennett, Derek R. Magee
ICRA
2006
IEEE
161views Robotics» more  ICRA 2006»
16 years 28 days ago
Quadruped Robot Obstacle Negotiation via Reinforcement Learning
— Legged robots can, in principle, traverse a large variety of obstacles and terrains. In this paper, we describe a successful application of reinforcement learning to the proble...
Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Sin...
CIKM
2005
Springer
16 years 13 days ago
Information retrieval and machine learning for probabilistic schema matching
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distribute...
Henrik Nottelmann, Umberto Straccia
ICAPR
2005
Springer
16 years 12 days ago
Learning Histopathological Microscopy
Histopathological tissue analysis by microscopy is a process that is subjective, prone to inter- and intra-observer variation. This, along with the problems associated with verbali...
James Shuttleworth, Alison Todman, Mark Norrish, M...