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SIGECOM
2009
ACM
114views ECommerce» more  SIGECOM 2009»
16 years 24 days ago
Policy teaching through reward function learning
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
Haoqi Zhang, David C. Parkes, Yiling Chen
SIGECOM
2009
ACM
112views ECommerce» more  SIGECOM 2009»
16 years 24 days ago
Network bargaining: algorithms and structural results
We consider models for bargaining in social networks, in which players are represented by vertices and edges represent bilateral opportunities for deals between pairs of players. ...
Tanmoy Chakraborty, Michael Kearns, Sanjeev Khanna
ICASSP
2007
IEEE
16 years 18 days ago
Markov Random Field Energy Minimization via Iterated Cross Entropy with Partition Strategy
This paper introduces a novel energy minimization method, namely iterated cross entropy with partition strategy (ICEPS), into the Markov random field theory. The solver, which is...
Jue Wu, Albert C. S. Chung
VTC
2007
IEEE
192views Communications» more  VTC 2007»
16 years 16 days ago
Access Scheduling Based on Time Water-Filling for Next Generation Wireless LANs
Opportunistic user access scheduling enhances the capacity of wireless networks by exploiting the multi user diversity. When frame aggregation is used, opportunistic schemes are no...
Ertugrul Necdet Ciftcioglu, Özgür Gü...
ATAL
2007
Springer
16 years 14 days ago
Incentive compatible ranking systems
Ranking systems are a fundamental ingredient of multi-agent environments and Internet Technologies. These settings can be viewed as social choice settings with two distinguished p...
Alon Altman, Moshe Tennenholtz