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Events for November 07, 2017
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Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Tue, Nov 07, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Francesco Bullo, University of California, Santa Barbara
Talk Title: Network Systems and Kuramoto Oscillators
Series: Fall 2017 Joint CSC@USC/CommNetS-MHI Seminar Series
Abstract: Network systems are mathematical models for the study of cooperation,
propagation, synchronization and other dynamical phenomena that arise
among interconnected agents. Network systems are widespread in science
as fundamental modeling tools. They also play a key growing role in
technology, e.g., in the design of power grids, cooperative robotic
behaviors and distributed computing algorithms. Their study pervades
applied mathematics.
This talk will review established and emerging frameworks for
modeling, analysis and design of network systems. I will survey the
available comprehensive theory for linear network systems and then
highlight selected nonlinear concepts. Next, I will focus on recent
developments on the analysis of security and transmission capacity in
power grids. I will review the Kuramoto model of coupled oscillators
and present recent results on its synchronization behavior.
Biography: Francesco Bullo is a Professor with the Mechanical
Engineering Department and the Center for Control, Dynamical Systems
and Computation at the University of California, Santa Barbara. He was
previously associated with the University of Padova, the California
Institute of Technology, and the University of Illinois. His research
interests focus on network systems and distributed control with
application to robotic coordination, power grids and social
networks. He is the coauthor of "Geometric Control of Mechanical
Systems" (Springer, 2004) and "Distributed Control of Robotic
Networks" (Princeton, 2009); his forthcoming "Lectures on Network
Systems" is available on his website. He received best paper awards
for his work in IEEE Control Systems, Automatica, SIAM Journal on
Control and Optimization, IEEE Transactions on Circuits and Systems,
and IEEE Transactions on Control of Network Systems. He is a Fellow of
IEEE and IFAC. He has served on the editorial boards of IEEE, SIAM,
and ESAIM journals, and will serve as IEEE CSS President in 2018.
Host: Ketan Savla, ksavla@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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Epstein Institute Seminar, ISE 651
Tue, Nov 07, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Daniel Bienstock, Professor, Columbia University
Talk Title: Using Robust Optimization to Incorporate Renewables in Electric Power Generation
Host: Prof. Jong-Shi Pang
More Information: November 7, 2017.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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CS Colloquium: Danqi Chen (Stanford) - From Reading Comprehension to Open-Domain Question Answering
Tue, Nov 07, 2017 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Danqi Chen, Stanford
Talk Title: From Reading Comprehension to Open-Domain Question Answering
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Research Colloquium.
Enabling a computer to understand a document so that it can answer comprehension questions is a central, yet unsolved, goal of NLP. This task of reading comprehension (i.e., question answering over a passage of text) has received a resurgence of interest, due to the creation of large-scale datasets and well-designed neural network models.
I will talk about how we build simple and effective models for advancing a machine's ability at reading comprehension. I'll focus on explaining the logical structure behind these neural architectures and discussing the capacities of these models as well as their limits.
Next I'll talk about how we combine state-of-the-art reading comprehension systems with traditional IR components to build a new generation of open-domain question answering systems. Our system is much simpler than traditional QA systems and able to answer questions efficiently over the full English Wikipedia and shows great promise on multiple QA benchmarks.
Biography: Danqi Chen is a Ph.D. candidate in Computer Science at Stanford University, advised by Christopher Manning. She works on deep learning for natural language processing, and is particularly interested in the intersection between text understanding and knowledge representation/reasoning. Her research spans from machine comprehension/question answering to knowledge base construction and syntactic parsing, with an emphasis on building principled yet highly effective models. She is a recipient of a Facebook Fellowship, a Microsoft Research Women's Fellowship and outstanding paper awards at ACL'16 and EMNLP'17. Previously, she received her B.S. with honors from Tsinghua University in 2012.
Host: Fei Sha
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Find More Jobs & Internships: Viterbi Career Gateway Workshop
Tue, Nov 07, 2017 @ 04:30 PM - 05:30 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Take part in a live tutorial to help you navigate Viterbi Career Gateway, a powerful job & internship search tool available ONLY to Viterbi students.
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: All Viterbi Students
Contact: RTH 218 Viterbi Career Connections