铸星闪耀 | 黄群：从中科院计算所到 MSRA，三个月访问投出一篇论文
微软亚洲研究院“铸星计划”旨在发掘和助力新一代青年学者，使其成为科研创新能力突出、走在世界科技前沿的学术带头人。于青年学者而言，这绝不是一场简单的访问：通过与顶尖研究员的亲密合作，学者们可以解决困扰许久的疑惑；依托最新、最丰富的数据集和强大的硬件资源，学者们能大大推进所做的科研项目；产业界独有的实际应用场景，也能帮助学者们解决研究落地过程中最真实的问题。 年轻、开拓、探索，是铸星计划的关键词；合作...
The productive software engineer with Dr. Tom Zimmermann
Episode 77, May 22, 2019- If you’re in software development, Dr. Tom Zimmermann, a senior researcher at Microsoft Research in Redmond, wants you to be more productive, and he’s here to help. How, you might ask? Well, while productivity can…
In the news | Microsoft Asia News Center
Microsoft Research Asia (MSRA) leads in 2019 WMT international machine translation competition
Microsoft Research Asia (MSRA) has achieved eight top places in the recent machine translation challenge organized by the 2019 fourth Conference on Machine Translation (WMT19), out of the eleven tasks it undertook. Overall, there are nineteen machine translation categories in…
In the news | Official Microsoft Blog
Harnessing big data in pediatric research to reimagine healthcare
For many of us, life begins in the hospital—and so does our health data. Health organizations worldwide are amassing more information than ever before from millions of patients throughout their lifetimes. Wrangling massive volumes of health data—from smart devices, medical…
In the news | The AI Blog
As search needs evolve, Microsoft makes AI tools for better search available to researchers and developers
Only a few years ago, web search was simple. Users typed a few words and waded through pages of results. Today, those same users may instead snap a picture on a phone and drop it into a search box or…
Microsoft Academic Analytics
To expose our users to the powerful insights provided by Microsoft Academic Graph (MAG), we have created analytics pages on the Microsoft Academic website and which focus on each primary ‘entity’ in our graph: Publications, Topics, Authors, Institutions, Journals, and…
Robust Language Representation Learning via Multi-task Knowledge Distillation
Language Representation Learning maps symbolic natural language texts (for example, words, phrases and sentences) to semantic vectors. Robust and universal language representations are crucial to achieving state-of-the-art results on many Natural Language Processing (NLP) tasks. Ensemble learning is one of…