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CORR
2010
Springer
127views Education» more  CORR 2010»
13 years 7 months ago
Learning Networks of Stochastic Differential Equations
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
José Bento, Morteza Ibrahimi, Andrea Montan...
CN
2002
102views more  CN 2002»
13 years 8 months ago
On the impact of soft handoff in cellular systems
We present a model for soft handoff in wireless cellular networks. In such networks, due to overlapping cells, handoffs are not instantaneous and multiple channels may be occupied...
Nidhi Hegde, Khosrow Sohraby
AAAI
2008
13 years 10 months ago
Latent Tree Models and Approximate Inference in Bayesian Networks
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Yi Wang, Nevin Lianwen Zhang, Tao Chen
ICML
2005
IEEE
14 years 9 months ago
Naive Bayes models for probability estimation
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
Daniel Lowd, Pedro Domingos
ICC
2007
IEEE
14 years 2 months ago
Voice Transmission Enhancing Model on Wireless Mesh Networks
Abstract— This paper initially shows ROHC and packet aggregation significantly improve the number of successful voice calls. However, the improvement does not include processor...
Sangkil Jung, Sangjin Hong, Kyungtae Kim, Junghoon...