Collaborative Research: AF: Small: New Directions in Algorithmic Replicability

科学中的可复制性和可再现性是关键问题。科学结果和实验是可重复和可复制的这一基本要求是科学发展和演变的核心。近年来，随着一些科学学科转向数据驱动的研究，这些担忧甚至被放大了，数据民主化和可负担的计算资源使指数级进步成为可能。可复制性/再现性问题已受到从一般媒体出版物到科学出版场所到专业和科学机构等广泛实体的注意。该项目侧重于解决涉及随机计算的科学研究中可重复性和再现性的关键需求。该项目将探索算法可复制性的新方向。该方法有三个方面：(1)在各种计算环境中定义和形式化可复制性的新概念，(2)开发可复制算法的设计方法，以及(3)调查与可复制性相关的限制和成本。这一倡议旨在从根本上为可复制和可再现计算领域做出贡献。它侧重于创新算法的发展和建立可复制性的下限。预计该研究将对机器学习和大数据分析等领域产生重大影响。除了这些直接领域之外，预计在这个项目下设计的原则和技术将影响更广泛的科学和技术领域。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Replicability and reproducibility in science are critical concerns. The fundamental requirement that scientific results and experiments be reproducible and replicable is central to the development and evolution of science. In recent years, these concerns have been even more amplified as several scientific disciplines are turning to data-driven research that enables exponential progress from data democratization and affordable computing resources. The replicability/reproducibility issue has received attention from a wide spectrum of entities ranging from general media publications to scientific publication venues to professional and scientific bodies. This project focuses on addressing the pivotal need for replicability and reproducibility in scientific research that involves randomized computations.The project will explore new directions in algorithmic replicability. The approach is threefold: (1) defining and formalizing new concepts of replicability across various computational contexts, (2) developing methodologies for the design of replicable algorithms, and (3) investigating the limitations and costs associated with replicability. This initiative seeks to contribute fundamentally to the field of replicable and reproducible computations. It focuses on the development of innovative algorithms and establishing lower bounds in replicability. The research is expected to have a significant impact on areas such as machine learning and large data analysis. Beyond these immediate fields, the principles and techniques devised under this project are anticipated to influence a broader spectrum of scientific and technological domains.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.