Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders
Authors: Alexey Drutsa
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We propose a novel algorithm that has strategic regret upper bound of O(log log T) for worst-case valuations. This pricing is based on our novel transformation that upgrades an algorithm designed for the setup with a single buyer to the multi-buyer case. We provide theoretical guarantees on the ability of a transformed algorithm to learn the valuation of a strategic buyer, which has uncertainty about the future due to the presence of rivals. ... We cannot directly apply the optimal RPPA algorithms (Drutsa, 2017b; 2018), because our bidders have incomplete information in the game, while the proofs of optimality of these algorithms strongly rely on complete information. |
| Researcher Affiliation | Collaboration | Alexey Drutsa 1 2 1Yandex, Moscow, Russia 2Faculty of Mechanics and Mathematics, Lomonosov Moscow State University, Moscow, Russia. |
| Pseudocode | Yes | Algorithm 1 Pseudo-code of a div-transformation div M(A1, sr) of a RPPA algorithm A1 ARPPA. |
| Open Source Code | No | The paper does not contain any explicit statement about providing open-source code for the described methodology, nor does it provide a link to a code repository. |
| Open Datasets | No | This paper is theoretical and does not describe experiments performed on a dataset, thus no information on dataset availability is provided. |
| Dataset Splits | No | This paper is theoretical and does not describe experiments with data. Therefore, it does not provide training/validation/test dataset splits. |
| Hardware Specification | No | This paper focuses on theoretical algorithm design and analysis. It does not describe any computational experiments or specify hardware used. |
| Software Dependencies | No | This paper describes a theoretical algorithm and provides pseudocode (Algorithm 1) but does not mention any specific software dependencies or version numbers required for implementation or experimentation. |
| Experiment Setup | No | This paper is theoretical and does not describe empirical experiments with specific hyperparameter values or system-level training settings. |