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Events for November 14, 2019

  • PhD Thesis Proposal - Michael Tsang

    Thu, Nov 14, 2019 @ 10:00 AM - 11:30 PM

    Computer Science

    University Calendar

    Title: Interpretable Machine Learning Models via Feature Interaction Discovery
    Date/Time: Thursday, November 14th 10-11:30am
    Location: SAL 322
    Candidate: Michael Tsang
    Committee: Prof. Yan Liu (adviser), Prof. Joseph Lim, Prof. Maja Mataric, Prof. Emily Putnam Hornstein, Prof. Xiang Ren

    The impact of machine learning prediction models has created a growing need for us to understand why they make their predictions. The interpretation of these models is important to reveal their fundamental behavior, to obtain scientific insights into data, and to help us trust automatic predictions. In this thesis proposal, we advance these directions via the problem of feature interaction discovery. We develop a way to interpret the feature interactions in feedforward neural networks by tracing their learned weights. We follow-up on this method and develop a way of learning transparent neural networks. Lastly, we investigate applications of this work on interpreting black-box models beyond feedforward neural networks, such as image/text classifiers and recommender systems. Throughout this presentation, we will explain the physical meaning and practical importance of our feature interaction interpretations.

    Location: Henry Salvatori Computer Science Center (SAL) - 322

    Audiences: Everyone Is Invited

    Posted By: Lizsl De Leon

  • CS Colloquium: Bryan Perozzi (Google AI) - Machine Learning on Graphs

    Thu, Nov 14, 2019 @ 03:30 PM - 04:50 PM

    Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Bryan Perozzi, Google AI

    Talk Title: Machine Learning on Graphs

    Series: Computer Science Colloquium

    Abstract: Machine Learning on Graphs (also known as Relational Learning, or Graph-Based Machine Learning) is a branch of ML which focuses on problems where the data items (nodes) contain discrete relationships (edges) between themselves (usually in addition to traditional real-valued feature vectors). The structure of these links between unlabelled data items can be leveraged for both semi-supervised learning and unsupervised learning algorithms.

    In this talk, I will provide an overview of the area, and some recent results from our team in clustering and representation learning. When appropriate, I will try to motivate our research with examples of real world problems.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.

    Biography: Bryan Perozzi is a Senior Research Scientist in Google AI's Algorithms and Optimization group, where he routinely analyzes some of the world's largest (and perhaps most interesting) graphs. Bryan's research focuses on developing techniques for learning expressive representations of relational data with neural networks. These scalable algorithms are useful for prediction tasks (classification/regression), pattern discovery, and anomaly detection in large networked data sets.

    Bryan is an author of 20+ peer-reviewed papers at leading conferences in machine learning and data mining (such as ICML, NeurIPS, KDD, and WWW). His doctoral work on learning network representations was awarded the 2017 KDD Dissertation Award. Bryan received his Ph.D. in Computer Science from Stony Brook University in 2016, and his M.S. from the Johns Hopkins University in 2011.

    Host: Sami Abu-El-Haija

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Posted By: Computer Science Department

  • Viterbi Impact Program: Reflection Session #2

    Thu, Nov 14, 2019 @ 03:30 PM - 04:30 PM

    Viterbi School of Engineering Student Organizations

    Workshops & Infosessions

    Viterbi Impact Program participants are invited to come together, connect with others in the program, and reflect/make meaning from their experiences volunteering.

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

    Audiences: Everyone Is Invited

    Posted By: Viterbi Undergraduate Programs

  • Sonny Astani Civil and Environmental Engineering Seminar

    Thu, Nov 14, 2019 @ 04:00 PM - 05:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars

    Speaker: Prof. Michael Kleeman, Ph.D., University of California, Davis

    Talk Title: Air Quality Implications of Various Energy Futures

    Abstract: TBA

    Host: Dr. George Ban-Weiss

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

  • Women in Engineering Meets Women in Industry

    Thu, Nov 14, 2019 @ 06:00 PM - 08:00 PM

    USC Viterbi School of Engineering, Viterbi School of Engineering Student Organizations

    Workshops & Infosessions

    Women in Engineering (WIE) Meets Women in Industry (WII) is a program designed to provide current Viterbi women the opportunity to meet with professional women in the field and gain insight on the unique challenges female engineers face. Through an engaging panel of Viterbi alumnae from varying backgrounds, participants can gain insight on the experience of transitioning from student life to professional careers, challenges women face in the workplace, and successes they-have achieved.

    We are excited to have 9 alumnae on the panel from LA Sanitation and Environment (LASAN), Boeing, Lockheed Martin, Northrop Grumman, The Aerospace Corporation, MOOG, the Viterbi School of Engineering, and more.

    This promises to be an amazing event with great conversations and mentorship from engineering women eager to meet you and share their experiences and wisdom! Please join us.

    RSVP at http://bit.ly/wiemeetswii19

    Dinner will be provided!

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

    Audiences: Everyone Is Invited

    Posted By: Monica De Los Santos