Jianfeng Gao Microsoft Research Paper

Partner Research Manager in Business AI at Microsoft AI & Research. From 2014 to 2017, I was Partner Research Manager at Deep Learning Technology Center (DLTC) at Microsoft Research, Redmond. I lead the development of AI solutions to Predictive Sales and Marketing. I also work on deep learning for text and image processing (see my DeepLearning2017 Tutorial and our IJCAI2016 Tutorial or MS internal site) and lead the development of AI systems for dialogue, machine reading comprehension (MRC), and question answering (QA).

We are hiring Researchers with strengths in ML and NLP, and Software Engineers with rich product experience.

DSSM [project site]: We have developed a series of deep semantic similarity models (DSSM, also a.k.a. Sent2Vec), which have been used for many text and image processing tasks, including web search [Huang et al. 2013, Shen et al. 2014], recommendation [Gao et al. 2014a], machine translation [Gao et al. 2014b], and QA [Yih et al. 2015].

MRC [project site]: We released a new MRC dataset, called MS MARCO; and have developed a series of reasoning networks for MRC, aka ReasoNet, ReasoNet with shared memory, and SAN.

Dialogue: We have developed neural network models for social bots trained on Twitter data [project site] and task-completion bots [project site]trained via reinforcement learning using a user simulator.

From 2006 to 2014, I was Principal Researcher at Natural Language Processing Group at Microsoft Research, Redmond. I worked on Web search, query understanding and reformulation, ads prediction, and statistical machine translation.

From 2005 to 2006, I was a research lead in Natural Interactive Services Division at Microsoft. I worked on Project X, an effort of developing natural user interface for Windows.

From 1999 to 2005, I was Research Lead in Natural Language Computing Group at Microsoft Research Asia. I, together with my colleagues, developed the first Chinese speech recognition system released with Microsoft Office, the Chinese/Japanese Input Method Editors (IME) which were the leading products in the market, and the natural language platform for Windows Vista.

Currently, I live with my family in Woodinville, WA.

Abstract

In this talk, I start with a brief introduction to the history of symbolic approaches to natural language processing (NLP), and why we move to neural approaches recently. Then I describes in detail the deep learning technologies that are recently developed for two areas of NLP tasks. First is a set of neural attention and inference models developed for machine reading comprehension and question answering. Second is the use of deep learning for various of dialogue agents, including task-completion bots and social chat bots.

Biography

Jianfeng Gao is Partner Research Manager in Deep Learning Technology Center (DLTC) at Microsoft Research, Redmond. He works on deep learning for text and image processing and leads the development of AI systems for machine reading comprehension (MRC), question answering (QA), dialogue, and business applications. From 2006 to 2014, he was Principal Researcher at Natural Language Processing Group at Microsoft Research, Redmond, where he worked on Web search, query understanding and reformulation, ads prediction, and statistical machine translation. From 2005 to 2006, he was a research lead in Natural Interactive Services Division at Microsoft, where he worked on Project X, an effort of developing natural user interface for Windows. From 2000 to 2005, he was Research Lead in Natural Language Computing Group at Microsoft Research Asia. He, together with his colleagues, developed the first Chinese speech recognition system released with Microsoft Office, the Chinese/Japanese Input Method Editors (IME) which were the leading products in the market, and the natural language platform for Windows Vista.

When:

March 31, 2017 @ 12:00 pm – 1:15 pm

2017-03-31T12:00:00-04:00

2017-03-31T13:15:00-04:00

Where:

Hackerman Hall B17
3400 N Charles St
Baltimore, MD 21218
USA

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