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ATAL
2007
Springer
16 years 24 days ago
Approximate state estimation in multiagent settings with continuous or large discrete state spaces
We present a new method for carrying out state estimation in multiagent settings that are characterized by continuous or large discrete state spaces. State estimation in multiagen...
Prashant Doshi
PE
1998
Springer
158views Optimization» more  PE 1998»
15 years 6 months ago
Asymptotic Approximations and Bottleneck Analysis in Product Form Queueing Networks with Large Populations
Asymptotic approximations are constructed for the performance measures of product form queueing networks consisting of single server, fixed rate nodes with large populations. The...
Charles Knessl, Charles Tier
PKDD
2010
Springer
212views Data Mining» more  PKDD 2010»
15 years 5 months ago
Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
ErHeng Zhong, Wei Fan, Qiang Yang, Olivier Versche...
SIGECOM
2009
ACM
216views ECommerce» more  SIGECOM 2009»
16 years 1 months ago
Approximate mechanism design without money
The literature on algorithmic mechanism design is mostly concerned with game-theoretic versions of optimization problems to which standard economic money-based mechanisms cannot b...
Ariel D. Procaccia, Moshe Tennenholtz
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
16 years 24 days ago
Convergence of stochastic search algorithms to gap-free pareto front approximations
Recently, a convergence proof of stochastic search algorithms toward finite size Pareto set approximations of continuous multi-objective optimization problems has been given. The...
Oliver Schütze, Marco Laumanns, Emilia Tantar...