Events for September 06, 2013
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AI Seminar
Fri, Sep 06, 2013 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Liang Huang, City University of New York (CUNY)
Talk Title: Scalable Training for Machine Translation Made Successful for the First Time
Abstract: While large-scale discriminative training has triumphed in many NLP problems, its definite success on machine translation has been largely elusive. Most recent efforts along this line are not scalable: they only train on the small dev set with an impoverished set of rather ââ¬Ådenseââ¬Â features. We instead present a very simple yet theoretically motivated approach by extending my recent framework of ââ¬Åviolation-fixing perceptronââ¬Â to the latent variable setting, and use forced decoding to compute the target derivations. Our method allows structured learning to scale, for the first time, to a large portion of the training data, which enables a rich set of sparse, lexicalized, and non-local features. Extensive experiments show very significant gains in BLEU (by at least +2.0) over MERT and PRO baselines with the help of over 20M sparse features.
Biography: Liang Huang is currently an Assistant Professor at the City University of New York (CUNY). He graduated in 2008 from Penn and has worked as a Research Scientist at Google and a Research Assistant Professor at USC/ISI. His work is mainly on the theoretical aspects (algorithms and formalisms) of computational linguistics, and related theoretical problems in machine learning. He has received a Best Paper Award at ACL 2008, several best paper nominations (ACL 2007, EMNLP 2008, and ACL 2010), two Google Faculty Research Awards (2010 and 2013), and a University Graduate Teaching Prize at Penn (2005).
Host: David Chiang
Location: Information Science Institute (ISI) - 6th floor conference room
Audiences: Everyone Is Invited
Contact: Kary LAU
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-Jeon-Hyung Kang:"LA-CTR: A Limited Attention Collaborative Topic Regression for Social Media"
Fri, Sep 06, 2013 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Jeon-Hyung Kang, USC/ISI
Talk Title: "LA-CTR: A Limited Attention Collaborative Topic Regression for Social Media"
Series: Natural Language Seminar
Abstract: Abstract: Probabilistic models can learn usersââ¬â¢ preferences from the history of their item adoptions on a social media site, and in turn, recommend new items to users based on learned preferences. However, current models ignore psychological factors that play an important role in shaping online social behavior. One such factor is attention, the mechanism that integrates perceptual and cognitive features to select the items the user will consciously process and may eventually adopt. Recent research has shown that people have finite attention, which constrains their online interactions, and that they divide their limited attention non-uniformly over other people. We propose a collaborative topic regression model that incorporates limited, non-uniformly divided attention. We show that the proposed model is able to learn more accurate user preferences than state-of-art models, which do not take human cognitive factors into account. Specifically we analyze voting on news items on the social news aggregator and show that our model is better able to predict held out votes than alternate models. Our study demonstrates that psycho-socially motivated models are better able to describe and predict observed behavior than models which only consider latent social structure and content.
Biography: Home Page:http://isi.edu/integration/people/kang/
Host: Yang Gao
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 689, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://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.
