Select a calendar:
Filter April Events by Event Type:
Events for April 25, 2014
-
NL Seminar-Partitioning Networks with Node Attributes by Compressing Information Flow
Fri, Apr 25, 2014 @ 03:00 AM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Linhong Zhu, USC/ISI
Talk Title: Partitioning Networks with Node Attributes by Compressing Information Flow
Series: Natural Language Seminar
Abstract: Real-world networks are often organized as modules or communities of similar nodes that serve as functional units. These networks are also rich in content, with nodes having distinguishing features or attributes. In order to discover a network's modular structure, it is necessary to take into account not only its links but also node attributes. We describe an information-theoretic method that identifies modules by compressing descriptions of information flow on a network. Our formulation introduces node content into the description of information flow, which we then minimize to discover groups of nodes with similar attributes that also tend to trap the flow of information. The method has several advantages: it is conceptually simple and does not require ad-hoc parameters to specify the number of modules or to control the relative contribution of links and node attributes to network structure. We apply the proposed method to partition real-world networks with known community structure. We demonstrate that adding node attributes helps recover the underlying community structure in content-rich networks more effectively than using links alone. In addition, we show that our method is faster and more accurate than alternative state-of-the-art algorithms.
Biography: Linhong Zhu is currently a Postdoctoral Research Associate at Information Sciences Institute, University of Southern California, under the supervision of Dr. Kristina Lerman and Dr. Aram Galstyan. Before that, she worked as a scientist-I at Institute for Infocomm Research Singapore from Oct 2010 to Jan 2013. She got her B Eng. Degree in Computer Science from University of Science and Technology of China in 2006 (2002-2006) and received her Ph.D. Degree in Computer Engineering from Nanyang Technological University (2006-2011). Her research interests focus on large-scale social network analysis and sentiment analysis.
Home Page:http://www.isi.edu/people/linhong/research
Host: Kevin Knight & Yang Gao
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, 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. -
ACL2014 Practice Talk: Kneser- Ney Smoothing on Expected Counts
Fri, Apr 25, 2014 @ 10:30 AM - 11:30 AM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Hui Zhang, USC/ISI
Talk Title: Kneser- Ney Smoothing on Expected Counts
Abstract: Widely used in speech and language processing, Kneser-Ney (KN) smoothing has consistently been shown to be one of the best-performing smoothing methods. However, KN smoothing assumes integer counts, limiting its potential usesâ⬔for example, inside Expectation-Maximization. In this paper, we propose a generaliza- tion of KN smoothing that operates on fractional counts, or, more precisely, on distributions over counts. We rederive all the steps of KN smoothing to operate on count distributions instead of integral counts, and apply it to two tasks where KN smoothing was not applicable before: one in language model adaptation, and the other in word alignment. In both cases, our method improves performance significantly.
Biography: Hui Zhang is a fourth year PhD student working with Professor David Chiang at the USC Information Sciences Institute. His main research interests are in statistical machine translation and machine learning.
He has focused on domain adaptation and smoothing techniques.
Home Page:
https://sites.google.com/site/zhangh1982/
Host: Yang Gao
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, 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.
