Learning fuzzy decision trees using integer programming. - Jason Rhuggenaath; Yingqian Zhang 001; Alp Akcay; Uzay Kaymak; Sicco Verwer (FUZZ-IEEE, 2018)

A PSO-based Algorithm for Reserve Price Optimization in Online Ad Auctions. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (CEC, 2019)

Optimizing reserve prices for publishers in online ad auctions. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (CIFEr, 2019)

Fuzzy Logic based Pricing combined with Adaptive Search for Reserve Price Optimization in Online Ad Auctions. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (FUZZ-IEEE, 2019)

Data-Driven Policy on Feasibility Determination for the Train Shunting Problem. - Paulo Roberto de Oliveira da Costa; Jason Rhuggenaath; Yingqian Zhang 001; Alp Akcay; Wan-Jui Lee; Uzay Kaymak (ECML/PKDD (3), 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 001; Uzay Kaymak (SMC, 2019)

Machine Learning based Simulation Optimisation for Trailer Management. - Dylan Rijnen; Jason Rhuggenaath; Paulo Roberto de Oliveira da Costa; Yingqian Zhang 001 (SMC, 2019)

Optimal display-ad allocation with guaranteed contracts and supply side platforms. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (Comput. Ind. Eng., 2019)

Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning. - Paulo R. de O. da Costa; Jason Rhuggenaath; Yingqian Zhang 001; Alp Akcay (ACML, 2020)

Dynamic Pricing Using Thompson Sampling with Fuzzy Events. - Jason Rhuggenaath; Paulo Roberto de Oliveira da Costa; Yingqian Zhang 001; Alp Akcay; Uzay Kaymak (IPMU (1), 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 001; Alp Akcay; Uzay Kaymak (ECML/PKDD (2), 2020)

Algorithms for slate bandits with non-separable reward functions. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (CoRR, 2020)

A Reward Shaping Approach for Reserve Price Optimization using Deep Reinforcement Learning. - Reza Refaei Afshar; Jason Rhuggenaath; Yingqian Zhang 001; Uzay Kaymak (IJCNN, 2021)

Data driven design for online industrial auctions. - Qing Chuan Ye; Jason Rhuggenaath; Yingqian Zhang 001; Sicco Verwer; Michiel Jurgen Hilgeman (Ann. Math. Artif. Intell., 2021)

Maximizing revenue for publishers using header bidding and ad exchange auctions. - Jason Rhuggenaath; Reza Refaei Afshar; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak; Fatih Çolak; Muratcan Tanyerli (Oper. Res. Lett., 2021)

Learning 2-Opt Heuristics for Routing Problems via Deep Reinforcement Learning. - Paulo da Costa 001; Jason Rhuggenaath; Yingqian Zhang 001; Alp Akcay; Uzay Kaymak (SN Comput. Sci., 2021)

Setting Reserve Prices in Second-Price Auctions with Unobserved Bids. - Jason Rhuggenaath; Alp Akcay; Yingqian Zhang 001; Uzay Kaymak (INFORMS J. Comput., 2022)

An Automated Deep Reinforcement Learning Pipeline for Dynamic Pricing. - Reza Refaei Afshar; Jason Rhuggenaath; Yingqian Zhang 001; Uzay Kaymak (IEEE Trans. Artif. Intell., 2023)