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» Probabilistic Neural Network Models for Sequential Data
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CORR
2010
Springer
118views Education» more  CORR 2010»
13 years 7 months ago
Large scale probabilistic available bandwidth estimation
The common utilization-based definition of available bandwidth and many of the existing tools to estimate it suffer from several important weaknesses: i) most tools report a point...
Frederic Thouin, Mark Coates, Michael G. Rabbat
FMSD
2002
92views more  FMSD 2002»
13 years 7 months ago
A Simple, Object-Based View of Multiprogramming
Object-based sequential programming has had a major impact on software engineering. However, object-based concurrent programming remains elusive as an effective programming tool. T...
Jayadev Misra
UAI
1998
13 years 9 months ago
The Bayesian Structural EM Algorithm
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
Nir Friedman
RECOMB
2004
Springer
14 years 8 months ago
Learning Regulatory Network Models that Represent Regulator States and Roles
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
Keith Noto, Mark Craven
ICANN
2003
Springer
14 years 1 months ago
The Spike Response Model: A Framework to Predict Neuronal Spike Trains
We propose a simple method to map a generic threshold model, namely the Spike Response Model, to artificial data of neuronal activity using a minimal amount of a priori informatio...
Renaud Jolivet, Timothy J. Lewis, Wulfram Gerstner