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» Learning Qualitative Models of Dynamic Systems
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TMI
2008
138views more  TMI 2008»
13 years 8 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
CIRA
2007
IEEE
179views Robotics» more  CIRA 2007»
14 years 2 months ago
Learning Tactic-Based Motion Models of a Moving Object with Particle Filtering
— Learning motion models of a moving object is a challenge for autonomous robots. We address the particular instance of parameter learning when tracking object motions in a switc...
Yang Gu, Manuela M. Veloso
ICONIP
2009
13 years 6 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
KDD
2000
ACM
114views Data Mining» more  KDD 2000»
14 years 2 days ago
Learning Prosodic Patterns for Mandarin Speech Synthesis
Higher quality synthesized speech is required for widespread use of text-to-speech (TTS) technology, and prosodic pattern is the key feature that makes synthetic speech sound unna...
Yiqiang Chen, Wen Gao, Tingshao Zhu
CIKM
2010
Springer
13 years 6 months ago
Mining topic-level influence in heterogeneous networks
Influence is a complex and subtle force that governs the dynamics of social networks as well as the behaviors of involved users. Understanding influence can benefit various applic...
Lu Liu, Jie Tang, Jiawei Han, Meng Jiang, Shiqiang...