6 papers · 1 filter
Robust personalized pricing under uncertainty of purchase probabilities
Shunnosuke Ikeda, Naoki Nishimura, Noriyoshi Sukegawa +1
This paper is concerned with personalized pricing models aimed at maximizing the expected revenues or profits for a single item. While it is essential for personalized pricing to p…
Fast solution to the fair ranking problem using the Sinkhorn algorithm
Yuki Uehara, Shunnosuke Ikeda, Naoki Nishimura +8
In two-sided marketplaces such as online flea markets, recommender systems for providing consumers with personalized item rankings play a key role in promoting transactions between…
Robust portfolio optimization for recommender systems considering uncertainty of estimated statistics
Tomoya Yanagi, Shunnosuke Ikeda, Yuichi Takano
This paper is concerned with portfolio optimization models for creating high-quality lists of recommended items to balance the accuracy and diversity of recommendations. However, t…
Container pre-marshalling problem minimizing CV@R under uncertainty of ship arrival times
Daiki Ikuma, Shunnosuke Ikeda, Noriyoshi Sukegawa +1
This paper is concerned with the container pre-marshalling problem, which involves relocating containers in the storage area so that they can be efficiently loaded onto ships witho…
Privacy-preserving recommender system using the data collaboration analysis for distributed datasets
Tomoya Yanagi, Shunnosuke Ikeda, Noriyoshi Sukegawa +1
In order to provide high-quality recommendations for users, it is desirable to share and integrate multiple datasets held by different parties. However, when sharing such distribut…
Interpretable Price Bounds Estimation with Shape Constraints in Price Optimization
Shunnosuke Ikeda, Naoki Nishimura, Shunji Umetani
This study addresses the interpretable estimation of price bounds in the context of price optimization. In recent years, price-optimization methods have become indispensable for ma…