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» Approximate Learning of Dynamic Models
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BMCBI
2008
130views more  BMCBI 2008»
15 years 2 months ago
Function approximation approach to the inference of reduced NGnet models of genetic networks
Background: The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of m...
Shuhei Kimura, Katsuki Sonoda, Soichiro Yamane, Hi...
ICDE
2006
IEEE
201views Database» more  ICDE 2006»
16 years 3 months ago
Approximate Data Collection in Sensor Networks using Probabilistic Models
Wireless sensor networks are proving to be useful in a variety of settings. A core challenge in these networks is to minimize energy consumption. Prior database research has propo...
David Chu, Amol Deshpande, Joseph M. Hellerstein, ...
UAI
2008
15 years 3 months ago
Continuous Time Dynamic Topic Models
In this paper, we develop the continuous time dynamic topic model (cDTM). The cDTM is a dynamic topic model that uses Brownian motion to model the latent topics through a sequenti...
Chong Wang, David M. Blei, David Heckerman
AAAI
2006
15 years 3 months ago
Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
The Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent parame...
David Wingate, Satinder P. Singh
ICML
2002
IEEE
16 years 3 months ago
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Carlos Guestrin, Relu Patrascu, Dale Schuurmans