Auto-bidding with Budget and ROI Constrained Buyers
Authors: Xiaodong Liu, Weiran Shen
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we conduct extensive experiments to empirically evaluate the effectiveness of our design. In this section, we conduct experiments based on an open data set and report the experiment results. |
| Researcher Affiliation | Academia | Gaoling School of Artificial Intelligence, Renmin University of China {xiaodong.liu, shenweiran}@ruc.edu.cn |
| Pseudocode | Yes | Algorithm 1: Finding the optimal βi |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described, nor does it provide a specific repository link or an explicit code release statement. |
| Open Datasets | Yes | Then we conduct experiments based on the open data set i Pin You [Liao et al., 2014]. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate the experiment. |
| Experiment Setup | Yes | The buyer s budget constraint is drawn randomly from a uniform distribution U[0, 3] and the ROI target is drawn randomly from a uniform distribution U[0, 5]. We randomly sample 10000 budget constraint and ROI target pairs. For each pair, we simulate 1,000,000 auctions and compute the average payment and the utility. the budget constraint is drawn randomly from uniform distribution U[0, 300] and the ROI target is drawn randomly from distribution U[0, 5]. We randomly sample 10000 budget constraint and ROI target pairs and simulate 1, 000, 000 auctions for each pair to compute the expected payment and utility. |