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ICASSP
2011
IEEE
14 years 5 months ago
Empirical divergence maximization for quantizer design: An analysis of approximation error
Empirical divergence maximization is an estimation method similar to empirical risk minimization whereby the Kullback-Leibler divergence is maximized over a class of functions tha...
Michael A. Lexa
AMAI
2004
Springer
15 years 6 months ago
Approximate Probabilistic Constraints and Risk-Sensitive Optimization Criteria in Markov Decision Processes
The majority of the work in the area of Markov decision processes has focused on expected values of rewards in the objective function and expected costs in the constraints. Althou...
Dmitri A. Dolgov, Edmund H. Durfee
STOC
2004
ACM
118views Algorithms» more  STOC 2004»
16 years 1 months ago
Boosted sampling: approximation algorithms for stochastic optimization
Several combinatorial optimization problems choose elements to minimize the total cost of constructing a feasible solution that satisfies requirements of clients. In the STEINER T...
Anupam Gupta, Martin Pál, R. Ravi, Amitabh ...
FORTE
2004
15 years 2 months ago
How Synchronisation Strategy Approximation in PEPA Implementations Affects Passage Time Performance Results
Passage time densities are useful performance measurements in stochastic systems. With them the modeller can extract probabilistic quality-of-service guarantees such as: the proba...
Jeremy T. Bradley, Stephen T. Gilmore, Nigel Thoma...
ATMN
1996
15 years 2 months ago
Traffic characterisation and modelling of VBR coded MPEG sources
This paper intends to study the characteristics of VBR MPEG sources and performs models for their traffic behaviour. Our analysis focuses on long-time MPEG video films, approximat...
Anastasios D. Doulamis, Nikolaos D. Doulamis, Geor...