Jason Rhuggenaath

According to our database, Jason Rhuggenaath authored at least 17 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

An Automated Deep Reinforcement Learning Pipeline for Dynamic Pricing.

Reza Refaei Afshar, Jason Rhuggenaath, Yingqian Zhang, Uzay Kaymak

IEEE Trans. Artif. Intell., June, 2023

2021

Learning 2-Opt Heuristics for Routing Problems via Deep Reinforcement Learning.

Paulo da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Uzay Kaymak

SN Comput. Sci., 2021

Maximizing revenue for publishers using header bidding and ad exchange auctions.

Jason Rhuggenaath, Reza Refaei Afshar, Alp Akcay, Yingqian Zhang, Uzay Kaymak, Fatih Çolak, Muratcan Tanyerli

Oper. Res. Lett., 2021

Data driven design for online industrial auctions.

Qing Chuan Ye, Jason Rhuggenaath, Yingqian Zhang, Sicco Verwer, Michiel Jurgen Hilgeman

Ann. Math. Artif. Intell., 2021

A Reward Shaping Approach for Reserve Price Optimization using Deep Reinforcement Learning.

Reza Refaei Afshar, Jason Rhuggenaath, Yingqian Zhang, Uzay Kaymak

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

Algorithms for slate bandits with non-separable reward functions.

Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak

CoRR, 2020

Low-Regret Algorithms for Strategic Buyers with Unknown Valuations in Repeated Posted-Price Auctions.

Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Yingqian Zhang, Alp Akcay, Uzay Kaymak

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Dynamic Pricing Using Thompson Sampling with Fuzzy Events.

Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Yingqian Zhang, Alp Akcay, Uzay Kaymak

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020

Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning.

Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay

Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019

Optimal display-ad allocation with guaranteed contracts and supply side platforms.

Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak

Comput. Ind. Eng., 2019

Machine Learning based Simulation Optimisation for Trailer Management.

Dylan Rijnen, Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Yingqian Zhang

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

A heuristic policy for dynamic pricing and demand learning with limited price changes and censored demand.

Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, Uzay Kaymak

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Data-Driven Policy on Feasibility Determination for the Train Shunting Problem.

Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Fuzzy Logic based Pricing combined with Adaptive Search for Reserve Price Optimization in Online Ad Auctions.

Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak

Proceedings of the 2019 IEEE International Conference on Fuzzy Systems, 2019

Optimizing reserve prices for publishers in online ad auctions.

Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak

Proceedings of the IEEE Conference on Computational Intelligence for Financial Engineering & Economics, 2019

A PSO-based Algorithm for Reserve Price Optimization in Online Ad Auctions.

Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak

Proceedings of the IEEE Congress on Evolutionary Computation, 2019

2018

Learning fuzzy decision trees using integer programming.

Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Uzay Kaymak, Sicco Verwer

Proceedings of the 2018 IEEE International Conference on Fuzzy Systems, 2018