[REVIEW]: PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization

[editorialbot]

Submitting author: @WilliamLwj (Wenjie Li)
Repository: https://github.com/WilliamLwj/PyXAB
Branch with paper.md (empty if default branch): paper
Version: v0.3.0
Editor: @drvinceknight
Reviewers: @Otomisin, @KBodolai
Archive: Pending

Status

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Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@Otomisin & @KBodolai, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
First of all you need to run this command in a separate comment to create the checklist:

@editorialbot generate my checklist

The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @drvinceknight know.

✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨

Checklists

📝 Checklist for @KBodolai

[editorialbot]

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.90  T=0.08 s (1445.7 files/s, 248507.4 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          72           1557           2390           3709
reStructuredText                33            603           1005            598
TeX                              1            124              2            439
Jupyter Notebook                 3              0           8598            329
Markdown                         2             82              0            320
YAML                             3             15             35             79
DOS Batch                        1              8              1             26
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                           116           2393          12038           5509
-------------------------------------------------------------------------------

Commit count by author:

   130	WilliamLi
    94	Williamlwj
    49	talhz
     8	Giggfitnesse
     3	William

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 1475

✅ The paper includes a Statement of need section

[editorialbot]

License info:

✅ License found: MIT License (Valid open source OSI approved license)

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1007/s10208-015-9296-2 is OK
- 10.1145/1374376.1374475 is OK
- 10.1287/moor.2021.1220 is OK
- 10.48550/ARXIV.1807.02811 is OK
- 10.1109/TIT.2015.2409256 is OK
- 10.48550/ARXIV.2205.15268 is OK

MISSING DOIs

- No DOI given, and none found for title: Hyperband: A Novel Bandit-Based Approach to Hyperp...
- 10.1007/bf00941892 may be a valid DOI for title: Lipschitzian optimization without the Lipschitz co...
- No DOI given, and none found for title: Derivative-Free Order-Robust Optimisation
- No DOI given, and none found for title: Contextual Bandits with Linear Payoff Functions
- 10.1007/978-3-030-64228-0_4 may be a valid DOI for title: Asset Management in Electrical Utilities in the Co...
- No DOI given, and none found for title: Google vizier: A service for black-box optimizatio...
- No DOI given, and none found for title: Prediction, Learning, and Games
- No DOI given, and none found for title: Bandit algorithms
- No DOI given, and none found for title: General parallel optimization a without metric
- No DOI given, and none found for title: Online stochastic optimization under correlated ba...
- No DOI given, and none found for title: Empirical Bernstein bounds and sample variance pen...
- No DOI given, and none found for title: Mathematics of statistical sequential decision mak...
- 10.1016/j.tcs.2009.01.016 may be a valid DOI for title: Exploration–exploitation tradeoff using variance e...
- No DOI given, and none found for title: χ-Armed Bandits
- No DOI given, and none found for title: Black-box optimization of noisy functions with unk...
- No DOI given, and none found for title: A simple parameter-free and adaptive approach to o...
- No DOI given, and none found for title: Optimistic Optimization of a Deterministic Functio...
- 10.1613/jair.4742 may be a valid DOI for title: Global continuous optimization with error bound an...
- No DOI given, and none found for title: Stochastic Simultaneous Optimistic Optimization
- 10.1007/978-3-540-72927-3_33 may be a valid DOI for title: Improved Rates for the Stochastic Continuum-Armed ...
- No DOI given, and none found for title: Optimum-statistical Collaboration Towards General ...
- 10.2139/ssrn.2661896 may be a valid DOI for title: Online decision making with high-dimensional covar...
- No DOI given, and none found for title: Federated Bayesian Optimization via Thompson Sampl...
- 10.1609/aaai.v35i11.17156 may be a valid DOI for title: Federated Multi-Armed Bandits
- No DOI given, and none found for title:  Federated Multi-armed Bandits with Personalizatio...
- No DOI given, and none found for title: Federated Linear Contextual Bandits
- No DOI given, and none found for title: Communication-efficient learning of deep networks ...
- No DOI given, and none found for title: Federated Online Sparse Decision Making
- 10.1145/3543516.3453919 may be a valid DOI for title: Federated bandit: A gossiping approach
- 10.1109/isit44484.2020.9174297 may be a valid DOI for title: Federated recommendation system via differential p...
- No DOI given, and none found for title: Differentially Private Federated Bayesian Optimiza...
- No DOI given, and none found for title: Federated Hyperparameter Tuning: Challenges, Basel...
- 10.3386/w29180 may be a valid DOI for title: Testing fractional doses of COVID-19 vaccines
- No DOI given, and none found for title: Semi-Supervised Multitask Learning
- 10.1109/tit.2023.3312308 may be a valid DOI for title: Lipschitz Bandits with Batched Feedback
- 10.1609/aaai.v30i1.10212 may be a valid DOI for title: Algorithms for Differentially Private Multi-Armed ...
- No DOI given, and none found for title: Batched Large-scale Bayesian Optimization in High-...
- No DOI given, and none found for title: Differentially Private Contextual Linear Bandits
- No DOI given, and none found for title: Differentially-Private Federated Linear Bandits
- No DOI given, and none found for title: Differential Privacy Under Continual Observation
- 10.1109/jproc.2015.2494218 may be a valid DOI for title: Taking the Human Out of the Loop: A Review of Baye...
- No DOI given, and none found for title: An Optimal Algorithm for Bandit and Zero-Order Con...

INVALID DOIs

- None

[drvinceknight]

👋🏼 @WilliamLwj @Otomisin, @KBodolai this is the review thread for the paper. All of our communications will happen here from now on.

As a reviewer, the first step is to create a checklist for your review by entering

@editorialbot generate my checklist

as the top of a new comment in this thread.

These checklists contain the JOSS requirements. As you go over the submission, please check any items that you feel have been satisfied. The first comment in this thread also contains links to the JOSS reviewer guidelines.

The JOSS review is different from most other journals. Our goal is to work with the authors to help them meet our criteria instead of merely passing judgment on the submission. As such, the reviewers are encouraged to submit issues and pull requests on the software repository. When doing so, please mention openjournals/joss-reviews#REVIEW_NUMBER so that a link is created to this thread (and I can keep an eye on what is happening). Please also feel free to comment and ask questions on this thread. In my experience, it is better to post comments/questions/suggestions as you come across them instead of waiting until you've reviewed the entire package.

We aim for reviews to be completed within about 2-4 weeks. Please let me know if any of you require some more time. We can also use EditorialBot (our bot) to set automatic reminders if you know you'll be away for a known period of time.

Please feel free to ping me (@drvinceknight) if you have any questions/concerns.

[KBodolai]

Review checklist for @KBodolai

Conflict of interest

• I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

• I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• Repository: Is the source code for this software available at the https://github.com/WilliamLwj/PyXAB?
• License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@WilliamLwj) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

• Installation: Does installation proceed as outlined in the documentation?
• Functionality: Have the functional claims of the software been confirmed?
• Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
• Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
• Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
• Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

• Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
• State of the field: Do the authors describe how this software compares to other commonly-used packages?
• Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?