Online Ad Allocation with Predictions
Authors: Fabian Spaeh, Alina Ene
NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We experimentally evaluate our algorithm on synthetic and real-world data on a wide range of predictions. Our algorithm is consistently outperforming the worst-case algorithm without predictions. |
| Researcher Affiliation | Academia | Fabian Spaeh Department of Computer Science Boston University fspaeh@bu.edu Alina Ene Department of Computer Science Boston University aene@bu.edu |
| Pseudocode | Yes | Algorithm 1 Exponential Averaging with Predictions |
| Open Source Code | No | The paper does not provide any statement or link regarding the public availability of its source code. |
| Open Datasets | Yes | We generate two instances for Display Ads based on the real-word datasets i Pin You (Zhang et al., 2014) and Yahoo (Yahoo, 2011). |
| Dataset Splits | No | The paper does not specify explicit training, validation, or test dataset splits (e.g., percentages or sample counts) for reproducibility, as the problem is online with impressions arriving sequentially. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., CPU, GPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not specify software dependencies with version numbers (e.g., Python, PyTorch, specific solver versions) needed to replicate the experiments. |
| Experiment Setup | Yes | For each predictor, we show the consistency (left) and robustness (right) for varying α. Figure 4 shows results for α = 5 with predictions of different quality, as described in the figure caption. We vary the sample fraction ϵ [0, 1] for the dual base algorithm and p [0, 1] for random and biased corruptions. We use synthetic data with 12 advertisers and 2000 impressions of 10 types, where we report the same quantities as in Figure 3. We assume a constant budget for each advertiser of 10 impressions as it makes for an interesting instance. |