Conferences, Lectures, & Seminars
Events for May
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AI Seminar-Natural Language Understanding with Incidental Supervision
Wed, May 15, 2019 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Dan Roth, University of Pennsylvania
Talk Title: Natural Language Understanding with Incidental Supervision
Series: Artificial Intelligence Seminar
Abstract: The fundamental issue underlying natural language understanding is that of semantics there is a need to move toward understanding natural language at an appropriate level of abstraction, beyond the word level, in order to support knowledge extraction, natural language understanding, and communication.
Machine Learning and Inference methods have become ubiquitous in our attempt to induce semantic representations of natural language and support decisions that depend on it. However, learning models that support high level tasks is difficult, partly since most they are very sparse and generating supervision signals for it does not scale. Consequently, making natural language understanding decisions, which typically depend on multiple, interdependent, models, becomes even more challenging.
I will describe some of our research on developing machine learning and inference methods in pursue of understanding natural language text. My focus will be on identifying and using incidental supervision signals in pursuing a range of semantics tasks, and I will point to some of the key challenges as well some possible directions for studying this problem from a principled perspective.
Biography: Dan Roth is the Eduardo D. Glandt Distinguished Professor at the Department of Computer and Information Science, University of Pennsylvania, and a Fellow of the AAAS, the ACM, AAAI, and the ACL.
In 2017 Roth was awarded the John McCarthy Award, the highest award the AI community gives to mid-career AI researchers. Roth was recognized for major conceptual and theoretical advances in the modeling of natural language understanding, machine learning, and reasoning.
Roth has published broadly in machine learning, natural language processing, knowledge representation and reasoning, and learning theory, and has developed advanced machine learning based tools for natural language applications that are being used widely. Until February 2017 Roth was the Editor-in-Chief of the Journal of Artificial Intelligence Research JAIR.
Prof. Roth received his B.A Summa cum laude in Mathematics from the Technion, Israel, and his Ph.D. in Computer Science from Harvard University in 1995.
Host: Nanyun Peng
More Info: https://nlg.isi.edu/nl-seminar
Webcast: https://bluejeans.com/s/1v5oL/Location: Information Science Institute (ISI) - Conf Rms #1135-1137
WebCast Link: https://bluejeans.com/s/1v5oL/
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: https://nlg.isi.edu/nl-seminar
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
NL Seminar-THE BLOCKS WORLD REDUX
Thu, May 16, 2019 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Martha Palmer , Univ of Colorado
Talk Title: THE BLOCKS WORLD REDUX
Series: Natural Language Seminar
Abstract: This talk will discuss some of the challenges arising from the Blocks World scenario in the DARPA Communicating with Computers program. The actions are very simple and concrete, such as Add a block to the tower. However, even in this restricted world, getting the appropriate contextual interpretation of a sentence can be challenging, especially with respect to spatial relations. The talk will review the progress we have made so far on collecting useful data and attempting to achieve the goal of contextual interpretation. To do this we bring to bear many resources, ranging from AMR parsing to Jerry Hobbs's axiomatization of object and action definitions, to our recent merger of James Pustejovsky's Generative Lexicon GL, and VerbNet VN, i.e., GL VN. A main focus of the talk will be the ways in which we are expanding AMR annotation to encompass spatial relations and also the recovery of implicit arguments. Both expansions play into the task of maintaining a discourse structure. The talk will conclude with both short term and long term goals for our collaborations on CwC, with respect to both AMR and GL-VN.
Biography: Martha Palmer is the Helen & Hubert Croft Endowed Professor of Engineering in the Computer Science Department, and an Arts & Sciences Professor of Distinction in the Linguistics Department, at the University of Colorado, with a split appointment. She is also an Institute of Cognitive Science Faculty Fellow, a co Director of CLEAR and an Association of Computational Linguistics ACL Fellow. She won an Outstanding Graduate Advisor 2014 Award, a Boulder Faculty Assembly 2010 Research Award and was the Director of the 2011 Linguistics Institute in Boulder, CO. Her research is focused on capturing elements of the meanings of words that can comprise automatic representations of complex sentences and documents in English, Chinese, Arabic, Hindi, and Urdu, funded by DARPA and NSF. A more recent focus is the application of these methods to biomedical journal articles and clinical notes, funded by NIH, and the geo and bio sciences, funded by NSF. She co edits LiLT, Linguistic Issues in Language Technology, and has been a co editor of the Journal of Natural Language Engineering and on the CLJ Editorial Board. She is a past President of ACL, past Chair of SIGLEX, was the Founding Chair of SIGHAN, and has well over 250 peer reviewed publications.
Host: Xusen Yin
More Info: https://nlg.isi.edu/nl-seminar
Webcast: https://bluejeans.com/s/ny0H5Location: Information Science Institute (ISI) - CR #689
WebCast Link: https://bluejeans.com/s/ny0H5
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: https://nlg.isi.edu/nl-seminar
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
NL Seminar-Quantifying the morphosyntactic content of Brown Clusters
Thu, May 30, 2019 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Manuel Ciosici, Aarhus University
Talk Title: Quantifying the morphosyntactic content of Brown Clusters
Series: Natural Language Seminar
Abstract: Brown and Exchange word clusters have long been successfully used as word representations in Natural Language Processing NLP systems. Their success has been attributed to their seeming ability to represent both semantic and syntactic information. Using corpora representing several language families, we test the hypothesis that Brown and Exchange word clusters are highly effective at encoding morphosyntactic information. Our experiments show that word clusters are highly capable of distinguishing Parts of Speech. We show that increases in Average Mutual Information, the clustering algorithms' optimization goal, are highly correlated with improvements in encoding of morphosyntactic information. Our results provide empirical evidence that downstream NLP systems addressing tasks dependent on morphosyntactic information can benefit from word cluster features.
Biography: Manuel is a soon to graduate Ph.D. student at Aarhus University, Denmark. His research is focused on understanding the kinds of information encoded in word representations and how that information can be used in downstream NLP applications.
Host: Xusen Yin
More Info: https://nlg.isi.edu/nl-seminar
Webcast: https://bluejeans.com/s/diiPj/Location: Information Science Institute (ISI) - CR #689
WebCast Link: https://bluejeans.com/s/diiPj/
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: https://nlg.isi.edu/nl-seminar
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
