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Events for August 30, 2013
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Meet USC: Admission Presentation, Campus Tour, & Engineering Talk
Fri, Aug 30, 2013
Viterbi School of Engineering Undergraduate Admission
Receptions & Special Events
This half day program is designed for prospective freshmen and family members. Meet USC includes an information session on the University and the Admission process; a student led walking tour of campus and a meeting with us in the Viterbi School. Meet USC is designed to answer all of your questions about USC, the application process and financial aid. Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m. Please visit https://esdweb.esd.usc.edu/unresrsvp/MeetUSC.aspx to check availability and make an appointment. Be sure to list an Engineering major as your "intended major" on the webform!
Location: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Everyone Is Invited
Contact: Viterbi Admission
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The W.V.T. Rusch Engineering Honors Colloquium
Fri, Aug 30, 2013 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
Student Activity
Jim Fiske, Founder and CTO of Gravity Power will speak about Using Gravity to Store Electricity.
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Christine Viterbi Admission & Student Affairs
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NL Seminar- Tomer Levinboim: "MKL and Low Rank
Fri, Aug 30, 2013 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Tomer Levinboim, USC/ISI
Talk Title: "MKL and Low Rank Multiplicative Shaping
Series: Natural Language Seminar
Abstract: Multiple Kernel Learning (MKL) has been a subject of intensive research over the past decade. Instead of searching for a good kernel function (implicitly, feature transformation of our data), the idea is to learn a combination of kernels that optimizes our objective. This formulation has found usage in feature selection and interpretability as well as (sometimes) leading to increased classification accuracy. In the talk, I will provide an introduction to MKL as well as present and compare a few MKL formulations for SVM classification. Given time, I will present our own non-linear (yet still convex) MKL formulation that linearly combines kernels that are first multiplied by low-rank matrices.
Biography: Home Page:
http://www-scf.usc.edu/~levinboi/
Host: Yang Gao
More Info: http://nlg.isi.edu/nl-seminar/
Location: 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
