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» A Modelling Framework for Functional Imagination
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ICML
2005
IEEE
16 years 4 months ago
Learning Gaussian processes from multiple tasks
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
Kai Yu, Volker Tresp, Anton Schwaighofer
ICML
1990
IEEE
15 years 7 months ago
Average Case Analysis of Conjunctive Learning Algorithms
We present an approach to modeling the average case behavior of learning algorithms. Our motivation is to predict the expected accuracy of learning algorithms as a function of the...
Michael J. Pazzani, Wendy Sarrett
ATAL
2010
Springer
15 years 4 months ago
Risk-sensitive planning in partially observable environments
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
Janusz Marecki, Pradeep Varakantham
TOG
2002
109views more  TOG 2002»
15 years 3 months ago
Level set surface editing operators
We present a level set framework for implementing editing operators for surfaces. Level set models are deformable implicit surfaces where the deformation of the surface is control...
Ken Museth, David E. Breen, Ross T. Whitaker, Alan...
ECCV
2010
Springer
15 years 7 months ago
Max-Margin Dictionary Learning for Multiclass Image Categorization
Abstract. Visual dictionary learning and base (binary) classifier training are two basic problems for the recently most popular image categorization framework, which is based on t...