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ORCIDReza Refaei Afshar
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2020 – today
- 2023
[j4]Yingqian Zhang
, Laurens Bliek, Paulo da Costa, Reza Refaei Afshar, Robbert Reijnen, Tom Catshoek, Daniël Vos, Sicco Verwer, Fynn Schmitt-Ulms, André Hottung, Tapan Shah, Meinolf Sellmann, Kevin Tierney, Carl Perreault-Lafleur, Caroline Leboeuf, Federico Bobbio, Justine Pepin, Warley Almeida Silva, Ricardo Gama, Hugo L. Fernandes, Martin Zaefferer, Manuel López-Ibáñez, Ekhine Irurozki:
The first AI4TSP competition: Learning to solve stochastic routing problems. Artif. Intell. 319: 103918 (2023)- [j3]Reza Refaei Afshar, Jason Rhuggenaath, Yingqian Zhang, Uzay Kaymak:
An Automated Deep Reinforcement Learning Pipeline for Dynamic Pricing. IEEE Trans. Artif. Intell. 4(3): 428-437 (2023) - 2022
- [j2]Reza Refaei Afshar, Yingqian Zhang, Uzay Kaymak:
Dynamic Ad Network Ordering Method Using Reinforcement Learning. Int. J. Comput. Intell. Syst. 15(1): 27 (2022) - [c9]Martijn Beeks, Reza Refaei Afshar, Yingqian Zhang, Remco M. Dijkman, Claudy van Dorst, Stijn de Looijer:
Deep Reinforcement Learning for a Multi-Objective Online Order Batching Problem. ICAPS 2022: 435-443 - [i3]Reza Refaei Afshar, Yingqian Zhang, Joaquin Vanschoren, Uzay Kaymak:
Automated Reinforcement Learning: An Overview. CoRR abs/2201.05000 (2022) - [i2]Laurens Bliek, Paulo da Costa, Reza Refaei Afshar, Yingqian Zhang, Tom Catshoek, Daniël Vos, Sicco Verwer, Fynn Schmitt-Ulms, André Hottung, Tapan Shah, Meinolf Sellmann, Kevin Tierney, Carl Perreault-Lafleur, Caroline Leboeuf, Federico Bobbio, Justine Pepin, Warley Almeida Silva, Ricardo Gama, Hugo L. Fernandes, Martin Zaefferer, Manuel López-Ibáñez, Ekhine Irurozki:
The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems. CoRR abs/2201.10453 (2022) - 2021
- [j1]Jason Rhuggenaath, Reza Refaei Afshar, Alp Akcay, Yingqian Zhang, Uzay Kaymak, Fatih Çolak, Muratcan Tanyerli:
Maximizing revenue for publishers using header bidding and ad exchange auctions. Oper. Res. Lett. 49(2): 250-256 (2021) - [c8]Reza Refaei Afshar, Jason Rhuggenaath, Yingqian Zhang, Uzay Kaymak:
A Reward Shaping Approach for Reserve Price Optimization using Deep Reinforcement Learning. IJCNN 2021: 1-8 - 2020
- [c7]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning. ACML 2020: 81-96 - [c6]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak, Ali Izzet Metin, Gönenç Seçil Tarakçioglu, Cosku Bas:
Reserve price optimization with header bidding and Ad Exchange. SMC 2020: 830-835 - [c5]Jeroen Verheugd, Paulo Roberto de Oliveira da Costa, Reza Refaei Afshar, Yingqian Zhang, Sjoerd Boersma:
Predicting Water Pipe Failures with a Recurrent Neural Hawkes Process Model. SMC 2020: 2628-2633 - [i1]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning. CoRR abs/2004.12117 (2020)
2010 – 2019
- 2019
- [c4]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. BNAIC/BENELEARN 2019 - [c3]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A Decision Support Method to Increase the Revenue of Ad Publishers in Waterfall Strategy. CIFEr 2019: 1-8 - [c2]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
Reinforcement Learning Method for Ad Networks Ordering in Real-Time Bidding. ICAART (Revised Selected Papers) 2019: 16-36 - [c1]Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. ICAART (2) 2019: 256-265
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