Human-Guided Statistical Relational Learning

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Hosted by IEEE Computer Society, Atlanta chapter


Recently there has been an increased interest in intelligent systems that effectively utilize human feedback. Traditional machine learners are reliant on a large amount of ideal training data. However, it is vital that learning systems working on complex, real-world tasks make use of expert knowledge to complement available data. Many intelligent systems require that the expert understand machine learning in order to provide useful knowledge. This talk will give an overview of relational learning techniques and then describe approaches that exploit the relational structure to incorporate expert knowledge in an intuitive way.



  Date and Time

  Location

  Contact

  Registration


  • 75 Fifth St. NW.
  • Atlanta, Georgia
  • United States 30308
  • Building: Centergy One
  • Room Number: 9th floor, room 9104
  • Click here for Map
  • can also contact: stephen.urban@gtri.gatech.edu

  • Registration closed


  Speakers

Dr. Phillip Odom of Georgia Tech Research Institute (GTRI)

Topic:

Human-Guided Statistical Relational Learning

Phillip Odom is a research scientist at the Georgia Tech Research Institute. He graduated with his PhD in Computer Science from Indiana University in 2017 under Professor Natarajan. His research areas of interest include statistical relational learning and decision-making with an emphasis on human-in-the-loop learners.

Biography:

Phillip Odom is a research scientist at the Georgia Tech Research Institute. He graduated with his PhD in Computer Science from Indiana University in 2017 under Professor Natarajan. His research areas of interest include statistical relational learning and decision-making with an emphasis on human-in-the-loop learners.

Email:

Address:Atlanta, Georgia, United States





Agenda

Doors open at 11:30am; lunch is provided.

The talk begins at noon and will wrap up around or before 1p.

We must vacate the space by 1:30p.

 


Lunch is provided!