Online Pricing with Strategic and Patient Buyers
Authors: Michal Feldman, Tomer Koren, Roi Livni, Yishay Mansour, Aviv Zohar
NeurIPS 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we give an algorithm that attains O(T2/3) regret over any sequence of T buyers with respect to the best fixed price in hindsight, and prove that no algorithm can perform better in the worst case. (i) We present an algorithm that achieves O( ˆ 1/3T2/3) additive regret in an adversarial setting, compared to the best fixed posted price in hindsight. (ii) We exhibit a matching lower bound of ( ˆ 1/3T2/3) regret. Algorithm 1: Online posted pricing algorithm |
| Researcher Affiliation | Collaboration | Michal Feldman Tel-Aviv University and MSR Herzliya michal.feldman@cs.tau.ac.il Tomer Koren Google Brain tkoren@google.com Roi Livni Princeton University rlivni@cs.princeton.edu Yishay Mansour Tel-Aviv University mansour@tau.ac.il Aviv Zohar Hebrew University of Jerusalem avivz@cs.huji.ac.il |
| Pseudocode | Yes | Algorithm 1: Online posted pricing algorithm |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described in this paper, nor does it state that code is available in supplementary materials or via a specific link. |
| Open Datasets | No | The paper is theoretical and does not involve the use of empirical datasets for training. Therefore, it does not provide concrete access information for a publicly available or open dataset. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for validation, training, or testing. Therefore, it does not provide specific dataset split information. |
| Hardware Specification | No | The paper is theoretical and does not mention any specific hardware details used for running experiments. |
| Software Dependencies | No | The paper is theoretical and does not describe any specific ancillary software details with version numbers needed to replicate an experiment. |
| Experiment Setup | No | The paper is theoretical and describes an algorithm but does not provide specific experimental setup details, such as concrete hyperparameter values or training configurations, as it does not report empirical experiments. |