PDF] Reproducibility via Crowdsourced Reverse Engineering: A Neural Network Case Study With DeepMind's Alpha Zero
Descrição
The significant success of reverse-engineering the important accomplishments of DeepMind's Alpha Zero exemplifies the leverage that can be achieved by a concerted effort to reproduce results. The reproducibility of scientific findings are an important hallmark of quality and integrity in research. The scientific method requires hypotheses to be subjected to the most crucial tests, and for the results to be consistent across independent trials. Therefore, a publication is expected to provide sufficient information for an objective evaluation of its methods and claims. This is particularly true for research supported by public funds, where transparency of findings are a form of return on public investment. Unfortunately, many publications fall short of this mark for various reasons, including unavoidable ones such as intellectual property protection and national security of the entity creating those findings. This is a particularly important and documented problem in medical research, and in machine learning. Fortunately for those seeking to overcome these difficulties, the internet makes it easier to share experiments, and allows for crowd-sourced reverse engineering. A case study of this capability in neural networks research is presented in this paper. The significant success of reverse-engineering the important accomplishments of DeepMind's Alpha Zero exemplifies the leverage that can be achieved by a concerted effort to reproduce results.
A Typology of AI Ethics Tools, Methods and Research, by Alex Moltzau
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A survey on data‐efficient algorithms in big data era, Journal of Big Data
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Learning Neural Models for Natural Language Processing in the Face of Distributional Shift – arXiv Vanity
![PDF] Reproducibility via Crowdsourced Reverse Engineering: A Neural Network Case Study With DeepMind's Alpha Zero](https://tanelp.github.io/neurips2021/thumbs/qb0qTdxPWzY.jpg)
NeurIPS 2021 papers
![PDF] Reproducibility via Crowdsourced Reverse Engineering: A Neural Network Case Study With DeepMind's Alpha Zero](https://edwardbetts.com/book_covers/003015.jpg)
Books: computer vision
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Learning Neural Models for Natural Language Processing in the Face of Distributional Shift – arXiv Vanity
2023 ICICT Proceedings, PDF, Machine Learning
![PDF] Reproducibility via Crowdsourced Reverse Engineering: A Neural Network Case Study With DeepMind's Alpha Zero](https://i1.rgstatic.net/publication/356819410_Simulation_Intelligence_Towards_a_New_Generation_of_Scientific_Methods/links/61b4f7d1a6251b553aaecb96/largepreview.png)
PDF) Simulation Intelligence: Towards a New Generation of Scientific Methods
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ICLR 2021
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Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery
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Emerging techniques in biological sciences - ScienceDirect
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A survey on data‐efficient algorithms in big data era, Journal of Big Data
![PDF] Reproducibility via Crowdsourced Reverse Engineering: A Neural Network Case Study With DeepMind's Alpha Zero](https://www.researchgate.net/profile/Daniel-Hier/publication/358475503/figure/fig1/AS:1142556444368897@1649418092866/A-timeline-of-AlphaGo-publications-and-significant-events-between-2016-and-2019_Q320.jpg)
PDF) Reproducing Neural Network Research Findings via Reverse Engineering: Replication of AlphaGo Zero by Crowdsourced Leela Zero
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