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ECML
2006
Springer
15 years 6 months ago
Learning Process Models with Missing Data
Abstract. In this paper, we review the task of inductive process modeling, which uses domain knowledge to compose explanatory models of continuous dynamic systems. Next we discuss ...
Will Bridewell, Pat Langley, Steve Racunas, Stuart...
ICML
2010
IEEE
15 years 3 months ago
The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling
The hierarchical Dirichlet process (HDP) is a Bayesian nonparametric mixed membership model--each data point is modeled with a collection of components of different proportions. T...
Sinead Williamson, Chong Wang, Katherine A. Heller...
118
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CSDA
2006
155views more  CSDA 2006»
15 years 2 months ago
Modelling the mean of a doubly stochastic Poisson process by functional data analysis
A new procedure for estimating the mean process of a doubly stochastic Poisson process is introduced. The proposed estimation is based on monotone piecewise cubic interpolation of...
P. R. Bouzas, Mariano J. Valderrama, Ana M. Aguile...
ECIS
2004
15 years 3 months ago
Towards a Process Model of Media Usage in Global Virtual Teams
In the networked world of today, global virtual teams (GVT) are becoming a common form of work structure. The geographic dispersion in GVT has led to members' high reliance o...
Juliana Sutanto, Chee Wei Phang, Atreyi Kankanhall...
SIGMETRICS
2010
ACM
181views Hardware» more  SIGMETRICS 2010»
15 years 2 months ago
A unified modeling framework for distributed resource allocation of general fork and join processing networks
This paper addresses the problem of distributed resource allocation in general fork and join processing networks. The problem is motivated by the complicated processing requiremen...
Haiquan (Chuck) Zhao, Cathy H. Xia, Zhen Liu, Dona...