Conferences, Lectures, & Seminars
Events for November
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NL Seminar-Structured Predictions: Practical Advancements and Applications in Natural Language Processing
Fri, Nov 03, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Kai-Wei Chang , UCLA
Talk Title: Structured Predictions: Practical Advancements and Applications in Natural Language Processing
Series: Natural Language Seminar
Abstract: Many machine learning problems involve making joint predictions over a set of mutually dependent output variables. The dependencies between output variables can be represented by a structure, such as a sequence, a tree, a clustering of nodes, or a graph. Structured prediction models have been proposed for problems of this type. In this talk, I will describe a collection of results that improve several aspects of these approaches. Our results lead to efficient and effective algorithms for learning structured prediction models, which, in turn, support weak supervision signals and improve training and evaluation speed. I will also discuss potential risks and challenges when using structured prediction models
Biography: Kai-Wei Chang is an assistant professor in the Department of Computer Science at the University of California, Los Angeles. He has published broadly in machine learning and natural language processing. His research has mainly focused on designing machine learning methods for handling large and complex data. He has been involved in developing several machine learning libraries, including LIBLINEAR, Vowpal Wabbit, and Illinois-SL. He was an assistant professor at the University of Virginia in 2016-2017. He obtained his Ph.D. from the University of Illinois at Urbana-Champaign in 2015 and was a post-doctoral researcher at Microsoft Research in 2016. Kai-Wei was awarded the EMNLP Best Long Paper Award 2017, KDD Best Paper Award 2010, and the Yahoo! Key Scientific Challenges Award 2011.
Host: Marjan Ghazvininejad and Kevin Knight
More Info: http://kwchang.net
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://kwchang.net
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-On Real-Time Graph Transducers
Fri, Nov 10, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Anssi Yli-Jyrä , Univ of Helsinki
Talk Title: On Real-Time Graph Transducers
Series: Natural Language Seminar
Abstract: Finite computers and universal computers. Often a practical solution combines both of these two extremes because formally powerful models are simulated by physical machines that approximate them. This is especially true for recurrent neural networks whose activation vector is the key to deeper understanding of their emergent finite state behavior. However, we currently have only a very loose characterization for the finite-state property in neural networks. In order to construct a hypothesis for a possible bottom up organization of the state space of activation vectors of RNNs, I compare neural networks with bounded Turing machines and finite state machines, and quote recent results on finite state models for semantic graphs. These models enjoy the nice closure properties of weighted finite state machines. In the end of the talk, I sketch my vision for neural networks that perform finite state graph transductions in real time. Such transductions would have a vast variety of applications in machine translation and semantic information retrieval involving big data.
Biography: Anssi Yli Jyrä has the titles of Adjunct Professor Docent in Language Technology at the University of Helsinki and Life Member of Clare Hall College at the University of Cambridge. He is currently a PI and a Research Fellow of the Academy of Finland in a project concerning universality of finite state syntax. He has published a handbook on Hebrew and Greek morpheme alignments in the Finnish Bible translation together with a group of Digital Humanists, and then served the Finnish Electronic Library at CSC IT Centre of Science where he built an internet harvester and a search engine for the Finnish WWW. In 2005, he earned his PhD from the University of Helsinki and then worked as a coordinator for the Language Bank of Finland at CSC. There he contributed to pushing his employer to what is now known as the CLARIN European Research Infrastructure Consortium. He became the first President of SIGFSM in 2009, after fostering and organizing FSMNLP conferences for several years. In 2012-2013, he served as a Subject Head of Language Technology in his home university before visiting the Speech Group at the Department of Engineering, Cambridge University. He has supervised theses and contributed to the theoretical basis of Helsinki Finite State Transducer HFST library. In his own research, Yli Jyrä constantly pursues unexplored areas, applying finite-state transducers to graphical language processing tasks such as autosegmental phonology, constraint interaction, and dependency syntax and neural semantics. He is a qualified teacher and interested in the occurrence of flow in agile programming and simultaneous translation.
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. -
NL Seminar-Learning and Reading
Fri, Nov 17, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Jonathan Gordon, USC/ISI
Talk Title: Learning and Reading
Series: Natural Language Seminar
Abstract: In recent years, a dramatic increase in the availability of digital text has created challenges and opportunities for learning for both humans and machines. My talk will describe research on learning commonsense knowledge from text despite our Gricean imperative to write down only what other people wouldn't know and using this for reasoning about language and the world. It will also address helping people to learn scientific knowledge by using implicit structure in a proliferation of articles, books, online courses, and other educational resources.
Biography: Jonathan Gordon is a postdoctoral researcher at the USC Information Sciences Institute, where he works with Jerry Hobbs and colleagues on the problems of learning and organizing knowledge from text. He completed a bachelor's degree in computer science at Vassar College and a Ph.D. in artificial intelligence at the University of Rochester, supervised by Lenhart Schubert.
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. -
NL Seminar-Algorithmic Bias in Artificial Intelligence: The Seen and Unseen Factors Influencing Machine Perception of Images and Language
Mon, Nov 20, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Margaret Mitchell, Google
Talk Title: Algorithmic Bias in Artificial Intelligence: The Seen and Unseen Factors Influencing Machine Perception of Images and Language
Series: Natural Language Seminar
Abstract: The success of machine learning has surged, with similar algorithmic approaches effectively solving a variety of human defined tasks. Tasks testing how well machines can perceive images and communicate about them have exposed strong effects of different types of bias, such as selection bias and dataset bias. In this talk, I will unpack some of these biases, and how they affect machine perception today.
Biography: Margaret Mitchell is a Senior Research Scientist in Google's Research & Machine Intelligence group, working on artificial intelligence. Her research generally involves vision-language and grounded language generation, focusing on how to evolve artificial intelligence towards positive goals. This includes research on helping computers to communicate based on what they can process, as well as projects to create assistive and clinical technology from the state of the art in AI.
Host: Marjan Ghazvininejad and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rms # 1135 and #1137, 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.
