The Experimentation Platform at Microsoft (ExP) has evolved over the past sixteen-plus years and now runs thousands of online A/B tests across most major Microsoft products every month. Throughout this time, we have seen impactful A/B tests on a huge…
微软亚洲研究院资深首席研究员谢幸博士获选2023 ACM Fellow
国际计算机学会（Association for Computing Machinery，简称 ACM）今天公布了2023年度 ACM Fellow 名单。本届入选的科研人员来自全球各地，并在包括人工智能技术、计算机图形学、网络安全、移动计算、软件分析和网络搜索等领域做出了突破性创新。其中，微软亚洲研究院资深首席研究员谢幸博士因其在空间数据挖掘和推荐系统方面的卓越贡献获选2023 ACM Fello...
Abstracts: January 25, 2024
| Gretchen Huizinga, Jordan Ash, and Dipendra Misra
On “Abstracts,” Jordan Ash & Dipendra Misra discuss the parameter reduction method LASER. Tune in to learn how selective removal of stored data alone can boost LLM performance, then sign up for Microsoft Research Forum for more on LASER &…
Research Focus: Week of January 22, 2024
Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. Join Microsoft Research Forum (opens in new tab) for a continuous exchange of…
Jianfeng Gao, Sumit Gulwani, Nicole Immorlica, Stefan Saroiu, Manik Varma, and Xing Xie are among the new class of 68 Association for Computing Machinery (ACM) fellows for their transformative contributions to computing science and technology.
Awards | Society for the Advancement of Economic Theory
Nicole Immorlica, 2023 SAET Economic Theory Fellow
Economic Theory Fellows are selected for their scientific excellence, originality, and leadership; high ethical standards; and scholarly and creative achievement. The primary qualification for fellowship is to have substantially advanced economic theory.
MetaOpt: Examining, explaining, and improving heuristic performance
| Behnaz Arzani, Pooria Namyar, Solal Pirelli, Ryan Beckett, Siva Kesava Reddy Kakarla, Srikanth Kandula, and Santiago Segarra
MetaOpt helps analyze, explain, and improve heuristic performance before deployment in production systems. Learn how it works, particularly in traffic engineering, packet scheduling, and VM placement.
In the news | Planet Labs
Accelerating Biodiversity and Ecosystem Reporting
Learn about feasible and cost-effective reporting with AI, earth observation, and ecosystem science (download the white paper).
大模型时代的计算机系统革新：更大规模、更分布式、更智能化
作者：杨懋 在计算机科学的诸多细分研究领域之中，计算机系统研究可能是最兼具“古典”与“摩登”特质的研究方向。说它古典，是因为计算机系统的雏形可以追溯到古代的算盘、算筹、数据表等计算工具，其发展远远早于软硬件、云计算、人工智能等技术的研究；至于摩登的一面，大数据、云计算等现代技术又促进了计算机系统的不断进化。传统计算机系统研究领域，如分布式系统理论和实践、编译优化、异构计算等成果，已在当今的大模型时...