[Colloquium] REMINDER: 2/16 Talks at TTIC: Danqi Chen, Stanford University

Fri Feb 16 09:54:58 CST 2018

 When:     Friday, February 16th at *10:30am*

Where:    TTIC, 6045 S Kenwood Avenue, 5th Floor, Room 526

Who:       Danqi Chen, Stanford University

Title:       Knowledge from Language via Deep Understanding

Abstract: Almost all of humanity's knowledge is now available online, but
the vast majority of it is principally encoded in the form of human
language explanations. In this talk, I explore novel neural network or deep
learning approaches that open up increased opportunities for getting a deep
understanding of natural language text. First, I show how distributed
representations enabled the building of a smaller, faster, better
dependency parser for finding the structure of human language sentences.
Then I show how related neural technologies can be used to improve the
construction of knowledge bases from text. However, maybe we don't need
this intermediate step and can directly gain knowledge and answer people's
questions from large textbases? In the third part, I explore doing this by
looking at a simple but highly effective neural architecture for question
answering.

Bio: Danqi Chen is a PhD student in Computer Science at Stanford
University, working with Christopher Manning on deep learning approaches to
Natural Language Processing. Her research centers on how computers can
achieve a deep understanding of human language and the information it
contains. Danqi received Outstanding Paper Awards at ACL 2016 and EMNLP
2017, a Facebook Fellowship, a Microsoft Research Women’s Fellowship and an
Outstanding Course Assistant Award from Stanford. She holds a B.E. with
honors from Tsinghua University.

Host: David McAllester <mcallester at ttic.edu>

Mary C. Marre
Administrative Assistant
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 504*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*

On Thu, Feb 15, 2018 at 11:00 AM, Mary Marre <mmarre at ttic.edu> wrote:

> When:     Friday, February 16th at *10:30am*
>
> Where:    TTIC, 6045 S Kenwood Avenue, 5th Floor, Room 526
>
> Who:       Danqi Chen, Stanford University
>
>
> Title:       Knowledge from Language via Deep Understanding
>
> Abstract: Almost all of humanity's knowledge is now available online, but
> the vast majority of it is principally encoded in the form of human
> language explanations. In this talk, I explore novel neural network or deep
> learning approaches that open up increased opportunities for getting a deep
> understanding of natural language text. First, I show how distributed
> representations enabled the building of a smaller, faster, better
> dependency parser for finding the structure of human language sentences.
> Then I show how related neural technologies can be used to improve the
> construction of knowledge bases from text. However, maybe we don't need
> this intermediate step and can directly gain knowledge and answer people's
> questions from large textbases? In the third part, I explore doing this by
> looking at a simple but highly effective neural architecture for question
> answering.
>
> Bio: Danqi Chen is a PhD student in Computer Science at Stanford
> University, working with Christopher Manning on deep learning approaches to
> Natural Language Processing. Her research centers on how computers can
> achieve a deep understanding of human language and the information it
> contains. Danqi received Outstanding Paper Awards at ACL 2016 and EMNLP
> 2017, a Facebook Fellowship, a Microsoft Research Women’s Fellowship and an
> Outstanding Course Assistant Award from Stanford. She holds a B.E. with
> honors from Tsinghua University.
>
>
> Host: David McAllester <mcallester at ttic.edu>
>
>
>
>
> Mary C. Marre
> Administrative Assistant
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue*
> *Room 504*
> *Chicago, IL  60637*
> *p:(773) 834-1757 <(773)%20834-1757>*
> *f: (773) 357-6970 <(773)%20357-6970>*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
> On Fri, Feb 9, 2018 at 3:35 PM, Mary Marre <mmarre at ttic.edu> wrote:
>
>> When:     Friday, February 16th at *10:30am*
>>
>> Where:    TTIC, 6045 S Kenwood Avenue, 5th Floor, Room 526
>>
>> Who:       Danqi Chen, Stanford University
>>
>>
>> Title:       Knowledge from Language via Deep Understanding
>>
>> Abstract: Almost all of humanity's knowledge is now available online, but
>> the vast majority of it is principally encoded in the form of human
>> language explanations. In this talk, I explore novel neural network or deep
>> learning approaches that open up increased opportunities for getting a deep
>> understanding of natural language text. First, I show how distributed
>> representations enabled the building of a smaller, faster, better
>> dependency parser for finding the structure of human language sentences.
>> Then I show how related neural technologies can be used to improve the
>> construction of knowledge bases from text. However, maybe we don't need
>> this intermediate step and can directly gain knowledge and answer people's
>> questions from large textbases? In the third part, I explore doing this by
>> looking at a simple but highly effective neural architecture for question
>> answering.
>>
>> Bio: Danqi Chen is a PhD student in Computer Science at Stanford
>> University, working with Christopher Manning on deep learning approaches to
>> Natural Language Processing. Her research centers on how computers can
>> achieve a deep understanding of human language and the information it
>> contains. Danqi received Outstanding Paper Awards at ACL 2016 and EMNLP
>> 2017, a Facebook Fellowship, a Microsoft Research Women’s Fellowship and an
>> Outstanding Course Assistant Award from Stanford. She holds a B.E. with
>> honors from Tsinghua University.
>>
>>
>> Host: David McAllester <mcallester at ttic.edu>
>>
>>
>>
>>
>> Mary C. Marre
>> Administrative Assistant
>> *Toyota Technological Institute*
>> *6045 S. Kenwood Avenue*
>> *Room 504*
>> *Chicago, IL  60637*
>> *p:(773) 834-1757 <(773)%20834-1757>*
>> *f: (773) 357-6970 <(773)%20357-6970>*
>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>
>
>
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