Reza Refaei Afshar

Orcid: 0000-0003-1558-8380

According to our database1, Reza Refaei Afshar authored at least 14 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
An Automated Deep Reinforcement Learning Pipeline for Dynamic Pricing.
IEEE Trans. Artif. Intell., June, 2023

The first AI4TSP competition: Learning to solve stochastic routing problems.
Artif. Intell., June, 2023

2022
Dynamic Ad Network Ordering Method Using Reinforcement Learning.
Int. J. Comput. Intell. Syst., 2022

The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems.
CoRR, 2022

Automated Reinforcement Learning: An Overview.
CoRR, 2022

Deep Reinforcement Learning for a Multi-Objective Online Order Batching Problem.
Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, 2022

2021
Maximizing revenue for publishers using header bidding and ad exchange auctions.
Oper. Res. Lett., 2021

A Reward Shaping Approach for Reserve Price Optimization using Deep Reinforcement Learning.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
Predicting Water Pipe Failures with a Recurrent Neural Hawkes Process Model.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Reserve price optimization with header bidding and Ad Exchange.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning.
Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019
Reinforcement Learning Method for Ad Networks Ordering in Real-Time Bidding.
Proceedings of the Agents and Artificial Intelligence - 11th International Conference, 2019

A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy.
Proceedings of the 11th International Conference on Agents and Artificial Intelligence, 2019

A Decision Support Method to Increase the Revenue of Ad Publishers in Waterfall Strategy.
Proceedings of the IEEE Conference on Computational Intelligence for Financial Engineering & Economics, 2019


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