Name
Abstract | ||
|---|---|---|
We study the dynamic pricing problem faced by a firm selling differentiated products. At each period, the firm receives a new product, which is described by a vector of features. The firm needs to choose prices, but it does not know a priori the market value of the different features. We first consider an algorithm that we call PolytopePricing, but prove that it incurs worst-case regret that scales exponentially in the dimensionality of the feature space. We then consider a closely related algorithm, EllipsoidPricing, and show it incurs low regret with regards to both the time horizon and the dimensionality of the feature space. For more details, we refer the reader to our full paper. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3055589.3055595 | SIGecom Exchanges |
Field | DocType | Volume |
Mathematical optimization,Feature vector,Economics,Mathematical economics,Time horizon,Regret,Dynamic pricing,Microeconomics,A priori and a posteriori,Curse of dimensionality,New product development,Product differentiation | Journal | 15 |
Issue | ISSN | Citations |
2 | 1551-9031 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maxime C. Cohen | 1 | 2 | 0.72 |
| Ilan Lobel | 2 | 240 | 17.78 |
| renato paes | 3 | 331 | 36.45 |