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150
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ICML
2010
IEEE
15 years 4 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
133
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TCOM
2008
126views more  TCOM 2008»
15 years 3 months ago
Distributed measurements for estimating and updating cellular system performance
We investigate the use of distributed measurements for estimating and updating the performance of a cellular system. Specifically, we discuss the number and placement of sensors in...
Liang Xiao, Larry J. Greenstein, Narayan B. Manday...
113
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DSN
2008
IEEE
15 years 10 months ago
Hot-spot prediction and alleviation in distributed stream processing applications
Many emerging distributed applications require the realtime processing of large amounts of data that are being updated continuously. Distributed stream processing systems offer a ...
Thomas Repantis, Vana Kalogeraki
153
Voted
SIGECOM
2010
ACM
174views ECommerce» more  SIGECOM 2010»
15 years 2 months ago
Aggregation and manipulation in prediction markets: effects of trading mechanism and information distribution
We conduct laboratory experiments on variants of market scoring rule prediction markets, under different information distribution patterns, in order to evaluate the efficiency an...
Lian Jian, Rahul Sami
127
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CDC
2008
IEEE
112views Control Systems» more  CDC 2008»
15 years 10 months ago
Application of the proximal center decomposition method to distributed model predictive control
Abstract— In this paper we present a dual-based decomposition method, called here the proximal center method, to solve distributed model predictive control (MPC) problems for cou...
Ion Necoara, Dang Doan, Johan A. K. Suykens