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Events for January 17, 2017

  • USC Stem Cell Seminar: Alex Meissner, Harvard Stem Cell Institute

    Tue, Jan 17, 2017 @ 11:00 AM - 12:00 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars

    Speaker: Alex Meissner, Harvard Stem Cell Institute

    Talk Title: TBD

    Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series

    Host: USC Stem Cell

    More Info: http://stemcell.usc.edu/events

    Webcast: http://keckmedia.usc.edu/stem-cell-seminar

    Location: Eli & Edythe Broad CIRM Center for Regenerative Medicine & Stem Cell Resch. (BCC) - First Floor Conference Room

    WebCast Link: http://keckmedia.usc.edu/stem-cell-seminar

    Audiences: Everyone Is Invited

    Contact: Cristy Lytal/USC Stem Cell

    Event Link: http://stemcell.usc.edu/events

  • CS Colloquium: Sungjin Ahn (University of Montreal) -Recent Advances and the Future of Recurrent Neural Networks

    Tue, Jan 17, 2017 @ 11:00 AM - 12:20 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Sungjin Ahn, University of Montreal

    Talk Title: Recent Advances and the Future of Recurrent Neural Networks

    Series: CS Colloquium

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    Although the recent resurgence of Recurrent Neural Networks (RNN) has achieved remarkable advances in sequence modeling, we are still missing many abilities of RNN necessary to model more challenging yet important natural phenomena. In this talk, I introduce some recent advances in this direction, focusing on two new RNN architectures: the Hierarchical Multiscale Recurrent Neural Networks (HM-RNN) and the Neural Knowledge Language Model (NKLM). In the HM-RNN, each layer in a multi-layered RNN learns different time-scales, adaptively to the inputs from the lower layer. The NKLM deals with the problem of incorporating factual knowledge provided by knowledge graph into RNNs. I argue the advantages of these models and then conclude the talk with a discussion on the key challenges that lie ahead.

    Biography: Sungjin Ahn is currently a postdoctoral researcher at the University of Montreal, working with Prof. Yoshua Bengio on deep learning and its applications. He received his Ph.D. in Computer Science at the University of California, Irvine, under the supervision of Prof. Max Welling. During his Ph.D. program, He co-developed the Stochastic Gradient MCMC algorithms and awarded two best paper awards from the International Conference on Machine Learning in 2012 and the ParLearning 2016, respectively. His research interests include deep learning (on recurrent neural networks, deep generative models), approximate Bayesian inference, and reinforcement learning.

    Host: Yan Liu

    Location: Ronald Tutor Hall of Engineering (RTH) - 217

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

  • Epstein Institute Seminar

    Tue, Jan 17, 2017 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars

    Speaker: Dr. Timothy Chan, University of Toronto

    Talk Title: Inverse Optimization: Closed-Form Solutions, Geometry and Goodness of Fit

    Host: Dr. Phebe Vayanos

    More Information: January 17, 2017_Chan.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Contact: Michele ISE

  • Writing Effective Resumes

    Tue, Jan 17, 2017 @ 05:00 PM - 06:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions

    Does your resume highlight the skills that will land an interview? Learn how to create a resume that will serve as the marketing tool that will get your foot inside industry's door!

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: All Viterbi

    Contact: RTH 218 Viterbi Career Connections