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» Nonlinear Markov Networks for Continuous Variables
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CLEIEJ
2007
152views more  CLEIEJ 2007»
15 years 1 months ago
Gene Expression Analysis using Markov Chains extracted from RNNs
Abstract. This paper present a new approach for the analysis of gene expression, by extracting a Markov Chain from trained Recurrent Neural Networks (RNNs). A lot of microarray dat...
Igor Lorenzato Almeida, Denise Regina Pechmann Sim...
UAI
2000
15 years 2 months ago
Gaussian Process Networks
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...
Nir Friedman, Iftach Nachman
INFOCOM
2010
IEEE
14 years 11 months ago
Resource Allocation over Network Dynamics without Timescale Separation
—We consider a widely applicable model of resource allocation where two sequences of events are coupled: on a continuous time axis (t), network dynamics evolve over time. On a di...
Alexandre Proutiere, Yung Yi, Tian Lan, Mung Chian...
CISS
2008
IEEE
15 years 7 months ago
Achieving network stability and user fairness through admission control of TCP connections
—This paper studies a network under TCP congestion control, in which the number of flows per user is explicitly taken into account. We present a control law for this variable th...
Andrés Ferragut, Fernando Paganini
JMLR
2010
202views more  JMLR 2010»
14 years 8 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...