# Advanced Bandit Algorithms Research

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/advanced-bandit-algorithms-research-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 274,793 |
| Description | This cluster of papers focuses on the optimization of multi-armed bandit problems, including topics such as Bayesian optimization, contextual bandits, online learning, convex optimization, Thompson sampling, regret analysis, Gaussian process optimization, hyperparameter optimization, and adversarial multi-armed bandits. |
| Domain | Social Sciences |
| Field | Decision Sciences |
| OpenAlex ID | https://openalex.org/T12101 |
| Works | 22,196 |

## Topic researchers

Showing 12 of 20.

- [Stuart Pocock](https://scholariq.org/researchers/stuart-pocock/)
- [Ilya Sutskever](https://scholariq.org/researchers/ilya-sutskever/)
- [David Haussler](https://scholariq.org/researchers/david-haussler/)
- [Demis Hassabis](https://scholariq.org/researchers/demis-hassabis/)
- [Michael I. Jordan](https://scholariq.org/researchers/michael-i-jordan/)
- [Oriol Vinyals](https://scholariq.org/researchers/oriol-vinyals/)
- [David Silver](https://scholariq.org/researchers/david-silver/)
- [Koray Kavukcuoglu](https://scholariq.org/researchers/koray-kavukcuoglu/)
- [Stephen Boyd](https://scholariq.org/researchers/stephen-boyd/)
- [Karen Simonyan](https://scholariq.org/researchers/karen-simonyan/)
- [Andrew Y. Ng](https://scholariq.org/researchers/andrew-y-ng/)
- [Léon Bottou](https://scholariq.org/researchers/leon-bottou/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.