Conferences, Lectures, & Seminars
Events for May
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AI Seminar
Thu, May 04, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Yan Liu, Associate Professor, USC
Talk Title: Deep Learning Models for Time Series Data Analysis with Applications to Healthcare
Abstract: Many emerging applications of big data involve time series data. We'll discuss a collection of deep learning models to effectively analyze and model large-scale time series data. We'll show experiment results to demonstrate the effectiveness of our models in healthcare.
Biography: Yan Liu is an associate professor in Computer Science Department at University of Southern California from 2010. Before that, she was a Research Staff Member at IBM Research. She received her M.Sc and Ph.D. degree from Carnegie Mellon University in 2004 and 2007. Her research interest includes developing scalable machine learning and data mining algorithms for time series data and structured data with applications to social media analysis, computational biology, climate modeling and health care. She has received several awards, including NSF CAREER Award, Okawa Foundation Research Award, ACM Dissertation Award Honorable Mention, Best Paper Award in SIAM Data Mining Conference, Yahoo, IBM and Facebook Faculty Award and the winner of several data mining competitions, such as KDD Cup and INFORMS data mining competition.
Host: Mayank Kejriwal
More Info: http://webcastermshd.isi.edu/Mediasite/Play/5447fbec7809488a9444c23f8b3619ce1d
Location: Information Science Institute (ISI) - 11th floor large conference room
Audiences: Everyone Is Invited
Contact: Kary LAU
Event Link: http://webcastermshd.isi.edu/Mediasite/Play/5447fbec7809488a9444c23f8b3619ce1d
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 - REPRESENTATION LEARNING FOR HUMAN AFFECT RECOGNITION-PhD Proposal Practice Talk
Fri, May 05, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Sayan Ghosh, USC/ICT
Talk Title: REPRESENTATION LEARNING FOR HUMAN AFFECT RECOGNITION-PhD Proposal Practice Talk
Series: Natural Language Seminar
Abstract: Recent advances in end-to-end representation learning have made impressive strides in achieving state-of-the-art results in perception problems on speech, image and natural language. However, the area of affect understanding has mostly relied on off-the-shelf features to solve problems in emotion recognition, multi-modal fusion and generative modeling of affective speech and language. The potential impact of representation learning approaches to this area remains ripe for exploration. My thesis proposal is an important step in this direction. Firstly, I present an overview of my work on AU (Action Unit) detection, speech emotion recognition and glottal inverse filtering through speech modeling. Secondly, I introduce Affect LM, a novel neural language model for affective text generation which exploits prior knowledge through a dictionary of emotionally colored words such as the LIWC tool. Finally, I state some upcoming problems in representation learning for affect from speech and multi-modal language modeling which I plan to work on for the remainder of my degree.
Biography: Sayan is a fourth-year PhD student at the University of Southern California, working at the Behavior Analytics and Machine Learning Group at the ICT Institute for Creative Technologies with Prof. Stefan Scherer. He is working on research towards building learning systems for better sensing of human behavior and emotion, and integrating deep learning techniques with human affect. His areas of interest include, but are not limited to deep learning, machine perception, affective computing, speech/signal processing, and generative modeling.
Host: Nima Pourdamghani
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. -
NL Seminar-BUILDING ADAPTABLE AND SCALABLE NATURAL LANGUAGE GENERATION SYSTEMS
Fri, May 26, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Yannis Konstas, Univ. of Washington
Talk Title: BUILDING ADAPTABLE AND SCALABLE NATURAL LANGUAGE GENERATION SYSTEMS
Series: Natural Language Seminar
Abstract: Traditionally, computers communicate with humans by converting computer readable input to human interpretable output, for example via graphical user interfaces. My research focuses on building programs that automatically generate textual output from computer-readable input. The majority of existing Natural Language Generation NLG systems use hard-wired rules or templates in order to capture the input for every different application and rely on small manually annotated corpora. In this talk, I will present a framework for building NLG systems using Neural Network architectures. The approach makes no domain specific modifications to the input and benefits from training on very large unannotated corpora. It achieves state of the art performance on a number of tasks, including generating text from meaning representations and source code. Such a system can have direct applications to intelligent conversation agents, source code assistant tools, and semantic based Machine Translation.
Biography: A postdoctoral researcher at the University of Washington, Seattle, collaborating with Prof. Luke Zettlemoyer since 2015. His main research interest focuses on the area of Natural Language Generation NLG with an emphasis on data-driven deep learning methods. He has received BSc in Computer Science from AUEB Greece in 2007, and MSc in Artificial Intelligence from the University of Edinburgh 2008. He continued his study at the University of Edinburgh and received his PhD. degree in 2014. He has previously worked as a Research Assistant at the University of Glasgow 2008, and as a postdoctoral researcher at the University of Edinburgh 2014.
Host: Marjan Ghazvininejad and Kevin Knight
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.
