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» On learning with dissimilarity functions
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AR
2006
86views more  AR 2006»
13 years 9 months ago
Learning for joint attention helped by functional development
Cognitive scientists and developmental psychologists have suggested that development in perceptual, motor and memory functions of human infants as well as adaptive evaluation by ca...
Yukie Nagai, Minoru Asada, Koh Hosoda
IWANN
1999
Springer
14 years 1 months ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
ICML
1998
IEEE
14 years 10 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
JMLR
2012
11 years 11 months ago
Structured Output Learning with High Order Loss Functions
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
Daniel Tarlow, Richard S. Zemel
ECAI
2008
Springer
13 years 11 months ago
Learning Functional Object-Categories from a Relational Spatio-Temporal Representation
Abstract. We propose a framework that learns functional objectes from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph t...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...