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CDC
2008
IEEE
147views Control Systems» more  CDC 2008»
16 years 1 months ago
Clustering neural spike trains with transient responses
— The detection of transient responses, i.e. non– stationarities, that arise in a varying and small fraction of the total number of neural spike trains recorded from chronicall...
John D. Hunter, Jianhong Wu, John G. Milton
HICSS
2007
IEEE
97views Biometrics» more  HICSS 2007»
16 years 1 months ago
Decision Support in Health Care via Root Evidence Sampling
— Bayesian networks play a key role in decision support within health care. Physicians rely on Bayesian networks to give medical treatment, generate what-if scenarios, and other ...
Benjamin B. Perry, Eli Faulkner
ICDM
2010
IEEE
186views Data Mining» more  ICDM 2010»
15 years 4 months ago
MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model
Human emotion is one important underlying force affecting and affected by the dynamics of social networks. An interesting question is "can we predict a person's mood base...
Yuan Zhang, Jie Tang, Jimeng Sun, Yiran Chen, Jing...
ICDM
2009
IEEE
183views Data Mining» more  ICDM 2009»
15 years 4 months ago
Multirelational Topic Models
In this paper we propose the multirelational topic model (MRTM) for multiple types of link modeling such as citation and coauthor links in document networks. In the citation networ...
Jia Zeng, William K. Cheung, Chun-hung Li, Jiming ...
AI
2002
Springer
15 years 6 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang