# Concentration Inequalities for Multinoulli Random Variables

arXiv: https://arxiv.org/abs/2001.11595 · HTML: https://mlsanity.com/paper/2001.11595/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jan 2020.

## Built on by (most cited first, 12 of 12)

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- [Reinforcement Learning for Markovian Bandits: Is Posterior Sampling more Scalable than Optimism?](https://mlsanity.com/paper/2106.08771/) (2021)
- [Fair Clustering via Hierarchical Fair-Dirichlet Process](https://mlsanity.com/paper/2305.17557/) (2023)
- [Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms](https://mlsanity.com/paper/2312.16860/) (2023)
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- [Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer](https://mlsanity.com/paper/2302.09273/) (2023)

## Abstract (arXiv)

We investigate concentration inequalities for Dirichlet and Multinomial random variables.
