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AROBOTS
2011
15 years 1 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
ICCS
2005
Springer
16 years 2 days ago
Modelling Dynamics of Genetic Networks as a Multiscale Process
A key phenomenon in the dynamics of genetic networks is the cell cycle. In the study of this phenomenon, an important task is to understand how many processes, acting on different...
Xilin Wei, Roderick V. N. Melnik, Gabriel Moreno-H...
LICS
2000
IEEE
15 years 11 months ago
Models for Name-Passing Processes: Interleaving and Causal
We study syntax-free models for name-passing processes. For interleaving semantics, we identify the indexing structure required of an early labelled transition system to support t...
Gian Luca Cattani, Peter Sewell
CEC
2005
IEEE
16 years 6 days ago
A study on polynomial regression and Gaussian process global surrogate model in hierarchical surrogate-assisted evolutionary alg
This paper presents a study on Hierarchical Surrogate-Assisted Evolutionary Algorithm (HSAEA) using different global surrogate models for solving computationally expensive optimiza...
Zongzhao Zhou, Yew-Soon Ong, My Hanh Nguyen, Dudy ...
CW
2003
IEEE
15 years 12 months ago
Development of a recommendation system with multiple subjective evaluation process models
Current BtoC recommendation services utilize consumers’ purchased log as criteria for selecting information, yet it includes little information of the reason why he bought the i...
Emi Yano, Emi Sueyoshi, Isao Shinohara, Toshikazu ...