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Events for the 3rd week of March


    Mon, Mar 13, 2017 @ 12:30 PM - 01:50 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars



    Host: Qifa Zhou

    Location: Olin Hall of Engineering (OHE) - 122

    Audiences: Everyone Is Invited

    Contact: Mischalgrace Diasanta

  • HackForHealth - Infosession

    Wed, Mar 15, 2017 @ 06:00 AM - 08:00 PM

    Thomas Lord Department of Computer Science

    Workshops & Infosessions

    Dear Trojan Family,

    In the spirit of the National Cancer Moonshot, The Kuhn Lab at USC is calling upon all Trojans to join to HackForHealth. Together we will spend a weekend building meaningful solutions to the problems that cancer patients and researchers face everyday. All are welcome, regardless of medical background or technical expertise.
    HackForHealth is a cancer-focused hackathon organized by the diverse team of researchers, physicians, students, and patients behind CancerBase -” a digital tool for cancer patients to securely track and share their medical data, powering research into the progression and treatment of cancer. We hope that you can join us from April 7-9 to interact with members of the cancer community and hack together solutions to help them, whether it be an app, website, gadget, or sketch. Projects will be judged by representatives from the National Cancer Institute. The prizes include cash and internship opportunities.

    Register today and let's beat cancer together!


    To learn more about HackForHealth, please attended one of our information sessions:

    UPC: March 8th, 2017 - 6pm at THH 202
    HSC: March 15th, 2017 - 6pm at NRT LG 503

    More Information: H4Hposter final.pdf

    Location: Harlyne J. Norris Research Tower (NRT) - LG 503

    Audiences: Everyone Is Invited

    Contact: Ryan Rozan

  • CS Yahoo! Machine Learning Seminar: Anshumali Shrivastava (Rice University) - Probabilistic Hashing for Scalable, Sustainable and Secure Machine Learning

    Fri, Mar 17, 2017 @ 10:30 AM - 11:30 AM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Anshumali Shrivastava, Rice University

    Talk Title: Probabilistic Hashing for Scalable, Sustainable and Secure Machine Learning

    Series: Yahoo! Labs Machine Learning Seminar Series

    Abstract: Large scale machine learning and data mining applications are constantly dealing with datasets at TB scale and the anticipation is that soon it will reach PB level. At this scale, simple data mining operations such as search, learning, and clustering become challenging.

    In this talk, we will start with a basic introduction to probabilistic hashing (or fingerprinting) and the classical LSH algorithm. Then I will present some of my recent adventures with probabilistic hashing in making large-scale machine learning practical. I will show how the
    idea of probabilistic hashing can be used to significantly reduce the computations in classical machine learning algorithms such Deep Learning (using our recent success with asymmetric hashing for inner products). I will highlight the computational bottleneck, i.e. the hashing time, and will show an efficient variant of minwise hashing. In the end, if time permits, I will demonstrate the use of probabilistic hashing for obtaining practical privacy-preserving

    Biography: Anshumali Shrivastava is an assistant professor in the computer science department at Rice University. His broad research interests include large scale machine learning, randomized algorithms for big data systems and graph mining. He is a recipient of 2017 NSF CAREER Award. His research on hashing inner products has won Best Paper Award at NIPS 2014 while his work on representing graphs got the Best Paper Award at IEEE/ACM ASONAM 2014. He obtained his PhD in computer science from Cornell University in 2015.

    Host: Yan Liu

    Location: Ronald Tutor Hall of Engineering (RTH) - 526

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

  • Seminars in Biomedical Engineering

    Fri, Mar 17, 2017 @ 02:30 PM - 04:30 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars



    Series: Seminars in BME (Lab Rotations)

    Host: Brent Liu, PhD

    Location: Corwin D. Denney Research Center (DRB) - 146

    Audiences: Everyone Is Invited

    Contact: Mischalgrace Diasanta

  • Heterogeneous Attribute Embedding and Sequence Modeling for Recommendation with Implicit Feedback

    Fri, Mar 17, 2017 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars

    Speaker: Kuan Liu, USC/ISI

    Talk Title: Heterogeneous Attribute Embedding and Sequence Modeling for Recommendation with Implicit Feedback

    Series: Natural Language Seminar

    Abstract: Incorporating implicit feedback into a recommender system is a challenging problem due to sparse and noisy observations. I will present our approaches that exploit heterogeneous attributes and sequence properties within the observations. We build a neural network framework to embed heterogeneous attributes in an end-to-end fashion, and apply the framework to three sequence-based models. Our methods achieve significant improvements on four large scale datasets compared to state-of-the-art baseline models 30 to 90 percent relative increase in NDCG. Experimental results show that attribute embedding and sequence modeling both lead to improvements and, further, that our novel output attribute layer plays a crucial role. I will conclude with our exploratory studies that investigate why sequence modeling works well in recommendation systems and advocate its use for large scale recommendation tasks.

    Biography: Kuan Liu is a fifth year Ph.D. student at ISI/USC working with Prof. Prem Natarajan. Before that, He received a bachelor degree from Tsinghua University with a major in Computer Science. His research interests include machine learning, large scale optimization, deep learning, and applications to recommender systems, network analysis.

    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/