Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints
Authors: Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco
NeurIPS 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The paper is theoretical and we do not have any experimental results. |
| Researcher Affiliation | Academia | Bocconi university Politecnico di Milano Sapienza University of Rome {martino.bernasconi,andrea.celli2}@unibocconi.it, matteo.castiglioni@polimi.it, federico.fusco@uniroma1.it |
| Pseudocode | Yes | Algorithm 1 and Algorithm 2 are present on page 2 and 3 respectively, providing structured pseudocode. |
| Open Source Code | No | The paper is theoretical and we do not have any experimental results. |
| Open Datasets | No | The paper is theoretical and we do not have any experimental results. |
| Dataset Splits | No | The paper is theoretical and we do not have any experimental results. |
| Hardware Specification | No | The paper is theoretical and we do not have any experimental results. |
| Software Dependencies | No | The paper is theoretical and we do not have any experimental results. |
| Experiment Setup | No | The paper is theoretical and we do not have any experimental results. |