Randomized Truthful Auctions with Learning Agents
Authors: Gagan Aggarwal, Anupam Gupta, Andres Perlroth, Grigoris Velegkas
NeurIPS 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The answer NA means that the paper does not include experiments. |
| Researcher Affiliation | Collaboration | Gagan Aggarwal Google Research gagana@google.com Anupam Gupta New York University, Google Research anupam.g@nyu.edu Andres Perlroth Google Research perlroth@google.com Grigoris Velegkas Yale University grigoris.velegkas@yale.edu |
| Pseudocode | Yes | ALGORITHM 1: Multiplicative Weights Update Algorithm. |
| Open Source Code | No | The answer NA means that paper does not include experiments requiring code. |
| Open Datasets | No | The paper does not include experiments or use datasets for training. |
| Dataset Splits | No | The paper does not include experiments or specify dataset splits for validation. |
| Hardware Specification | No | The paper does not include experiments and therefore does not provide hardware specifications. |
| Software Dependencies | No | The paper does not include experiments and therefore does not provide specific software dependencies with version numbers for replication. |
| Experiment Setup | No | The paper does not include experiments and therefore does not provide specific experimental setup details like hyperparameters. |