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» Convergence rates in monotone separable stochastic networks
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JMLR
2008
230views more  JMLR 2008»
13 years 8 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
PE
2002
Springer
176views Optimization» more  PE 2002»
13 years 8 months ago
Effective bandwidth estimation and testing for Markov sources
This work addresses the resource sharing problem in broadband communication networks that can guarantee some quality of service (QoS), and develops some results about data source ...
Juan Pechiar, Gonzalo Perera, María Simon
CORR
2010
Springer
338views Education» more  CORR 2010»
13 years 8 months ago
Optimal Distributed P2P Streaming under Node Degree Bounds
We study the problem of maximizing the broadcast rate in peer-to-peer (P2P) systems under node degree bounds, i.e., the number of neighbors a node can simultaneously connect to is ...
Shaoquan Zhang, Ziyu Shao, Minghua Chen
INFOCOM
2010
IEEE
13 years 7 months ago
Distributed Opportunistic Scheduling for Ad-Hoc Communications Under Delay Constraints
—With the convergence of multimedia applications and wireless communications, there is an urgent need for developing new scheduling algorithms to support real-time traffic with ...
Sheu-Sheu Tan, Dong Zheng, Junshan Zhang, James R....
TMC
2010
130views more  TMC 2010»
13 years 6 months ago
Efficient Coverage Maintenance Based on Probabilistic Distributed Detection
—Many wireless sensor networks require sufficient sensing coverage over long periods of time. To conserve energy, a coverage maintenance protocol achieves desired coverage by act...
Guoliang Xing, Xiangmao Chang, Chenyang Lu, Jianpi...