Seminar Announcement

Training Acceleration for Distributed Machine Learning Applications at Scale: A Network-Centric Approach.

  • Speaker: Dr. Grace Hui Yang
  • Georgetown University, Department of Computer Science
  • Date: Friday, September 7, 2018
  • Time: 1:00pm - 2:00pm
  • Location: Room T3 (NVC)

Abstract

In modern Information Retrieval (IR), users, data, and systems are often highly interactive and exhibit dynamic characteristics which are ignored by conventional approaches. What is missing is an ability for the retrieval models to change over time and be responsive to stimuli in the environment. This talk presents our up-to-date research on statistical modeling of dynamic search. The talk introduces a range of retrieval models and evaluation techniques that dynamically adjust themselves based on the signals collected over a long time spans from dynamic behaviors in documents, users, tasks and relevance judgments. The talk highlights how we model information seeking using a variety of reinforcement learning methods and achieve high accuracy in the TREC Session and TREC Dynamic Domain Tracks. The talk also gives perspectives on future directions in dynamic IR.

Speaker's Biography

Dr. Grace Hui Yang is an Associate Professor in the Department of Computer Science at Georgetown University. Dr. Yang is leading the InfoSense (Information Retrieval and Sense-Making) group at Georgetown University, Washington D.C., U.S.A.. Dr. Yang obtained her Ph.D. from the Language Technologies Institute, Carnegie Mellon University in 2011. Dr. Yang's current research interests include deep reinforcement learning, dynamic information retrieval, search engine evaluation, privacy-preserving information retrieval, internet of things, and information organization. Prior to this, she has conducted research on question answering, ontology construction, near-duplicate detection, multimedia information retrieval and opinion and sentiment detection. Dr. Yang's research has been supported by the Defense Advanced Defense Advanced Research Projects Agency and the National Science Foundation. Dr. Yang is a recipient of the prestigious National Science Foundation (NSF) Faculty Early Career Development Program (CAREER) Award. Dr. Yang has co-chaired SIGIR 2013 and 2014 Doctoral Consortiums, SIGIR 2017 Workshop, WSDM 2017 Workshop, ICTIR 2017 Workshop, CIKM 2015 Tutorial, ICTIR 2018 Short Paper and SIGIR 2018 Demonstration Paper Program Committees. Dr. Yang served on the editorial board of Information Retrieval Journal from 2014 to 2017. She has served as an area chair/senior program committee member for SIGIR 2014-present, WSDM 2018-present, ECIR 2017 and for ACL 2016. Dr. Yang also co-organized the Text Retrieval Conference (TREC) Dynamic Domain Track from 2015 to 2017 and led the effort for SIGIR privacy-preserving information retrieval workshops from 2014 to 2016.