# Online Learning for Min Sum Set Cover and Pandora's Box

@inproceedings{Gergatsouli2022OnlineLF, title={Online Learning for Min Sum Set Cover and Pandora's Box}, author={Evangelia Gergatsouli and Christos Tzamos}, booktitle={International Conference on Machine Learning}, year={2022} }

Two central problems in Stochastic Optimization are M IN S UM S ET C OVER and P ANDORA ’ S B OX . In P ANDORA ’ S B OX , we are presented with n boxes, each containing an unknown value and the goal is to open the boxes in some order to minimize the sum of the search cost and the small-est value found. Given a distribution of value vectors, we are asked to identify a near-optimal search order. M IN S UM S ET C OVER corresponds to the case where values are either 0 or inﬁn-ity. In this work, we…

## 2 Citations

### Contextual Pandora's Box

- Computer ScienceArXiv
- 2022

A no-regret algorithm that performs comparably well to the optimal algorithm which knows all prior distributions exactly, even in the bandit setting where the algorithm never learns the values of the alternatives that were not explored.

### Bandit Algorithms for Prophet Inequality and Pandora's Box

- Computer ScienceArXiv
- 2022

The main technique is to design a regret upper bound that is learnable while playing low-regret Bandit policies, which gives near-optimal total regret algorithms for both Prophet Inequality and Pandora’s Box.

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