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ORCID28th ASMTA 2024: Venice, Italy
- Arnaud Devos
, András Horváth, Sabina Rossi:
Analytical and Stochastic Modelling Techniques and Applications - 28th International Conference, ASMTA 2024, Venice, Italy, June 14, 2024, Proceedings. Lecture Notes in Computer Science 14826, Springer 2025, ISBN 978-3-031-70752-0 - Fabian Michel, Markus Siegle:
Markov Chain Aggregation with Error Bounds on Transient Distributions. 1-17 - Jean-Michel Fourneau, Moyi Yang:
Strong Aggregation in the Stochastic Matching Model with Random Discipline. 18-32 - Vincenzo Mancuso, Paolo Castagno, Leonardo Badia, Matteo Sereno, Marco Ajmone Marsan:
Optimal Allocation of Tasks to Networked Computing Facilities. 33-50 - Caitlin Vanden Bussche, Arnaud Devos, Sabine Wittevrongel, Dieter Fiems:
Revenue Management for Parallel Services with Fully Observable Queues. 51-66 - Francisco Robledo, Urtzi Ayesta, Konstantin Avrachenkov:
Deep Reinforcement Learning for Weakly Coupled MDP's with Continuous Actions. 67-80 - Dániel Szekeres, Kristóf Marussy, István Majzik:
A Lazy Abstraction Algorithm for Markov Decision Processes - Theory and Initial Evaluation. 81-96 - Keishin Tsutsumi, Tuan Phung-Duc, Hong Linh Truong:
Queueing Analysis of an Ensemble Machine Learning System. 97-111 - Illés Horváth, Márton Mészáros:
Analysis of Load Balancing Prioritization for Heterogeneous M/M/c/K Server Clusters in the Stationary Mean-Field Regime. 112-131 - Peter Buchholz, András Mészáros, Miklós Telek:
An Algebraic Proof of the Relation of Markov Fluid Queues and QBD Processes. 132-147 - Adityo Anggraito, Diletta Olliaro, Marco Ajmone Marsan, Andrea Marin:
Stability Condition for the Multi-server Job Queuing Model: Sensitivity Analysis. 148-163
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