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Events for September 05, 2017
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CS Colloquium: Ian Goodfellow (Google) - Generative Adversarial Networks
Tue, Sep 05, 2017 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ian Goodfellow, Google
Talk Title: Generative Adversarial Networks
Series: NVIDIA Distinguished Lecture Series in Machine Learning
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Generative adversarial networks (GANs) are machine learning models that are able to imagine new data, such as images, given a set of training data. They solve difficult approximate probabilistic computations using game theory. A generator network competes to fool a discriminator network in a game whose Nash equilibrium corresponds to recovering the probability distribution that generated the training data. GANs open many possibilities for machine learning algorithms.
Rather than associating input values in the training set with specific output values, GANs are able to learn to evaluate whether a particular output was one of many potential acceptable outputs or not.
Part of NVIDIA Distinguished Lecture Series in Machine Learning.
Biography: Ian Goodfellow (PhD in machine learning, University of Montreal, 2014) is a research scientist at Google. His research interests include most deep learning topics, especially generative models and machine learning security and privacy. He invented generative adversarial networks, was an influential early researcher studying adversarial examples, and is the lead author of the MIT Press textbook Deep Learning (www.deeplearningbook.org). He runs the Self-Organizing Conference on Machine Learning, which was founded at OpenAI in 2016.
Host: Yan Liu
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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Epstein Institute Seminar, ISE 651
Tue, Sep 05, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Lijuan Xu, Sr. Quantitative Analyst, Google
Talk Title: Being a Data Scientist in Tech
Host: Prof. Qiang Huang
More Information: September 5, 2017.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - GER 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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PhD Defense: Compression of Signal on Graphs with Application to Image and Video Coding
Tue, Sep 05, 2017 @ 04:00 PM - 06:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Workshops & Infosessions
Graph is a generic data structure that is useful in representing signals in various applications. In this thesis, we discuss several transform designs based on graph representation and the application in multimedia compression. Graphs can adapt to local characteristics, e.g. edges, and therefore provide more flexibilities than conventional transforms, e.g. Discrete Cosine Transform(DCT). A frequency interpretation for signal on graphs can be derived using Graph Fourier Transform (GFT). By properly adjusting the graph structure based on signal characteristics, GFT can provide compact representation even for signals with discontinuities. However, the transform requires high complexity in implementation, making it less applicable in signals of large size, e.g. video sequences. In our work, we develop a transform coding scheme based on a low complexity lifting transform on graphs. More specifically, we focus on two problems in the design of lifting transform, namely the design of bipartition and bipartite graph approximation. For the application, we consider two types of multimedia signals, including regular signals on 2D grid and signals that are irregularly distributed. For the former one, we consider the compression of intra-predicted video residuals. The data contain significant edge structures, which are difficult to be represented efficiently with existing transform coding standards. We also discuss different types of edge models for intra and inter-predicted video residuals in terms of the coding efficiency in GFT. For the other type of signal, we discuss the coding scheme for un-demosaicked light field images. Without demosaicking from the raw data captured using Color Filter Array (CFA) to full-color sub-aperture images, we can avoid large redundancies introduced from color interpolation. However, the pixels of each color channel will be distributed irregularly within each sub-aperture image, and therefore motivates the application of graph representation. A novel intra-prediction scheme and graph construction based on sparsely distributed pixels are proposed. Theoretical interpretation and comprehensive experimental results are presented for proposed methods.
More Information: Yung-Hsuan Chao Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
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Viterbi Progressive Degree Program Info Session
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Tue, Sep 05, 2017 @ 05:00 PM - 06:00 PM
Viterbi School of Engineering Graduate Admission, Viterbi School of Engineering Student Affairs, Viterbi School of Engineering Student Organizations
Workshops & Infosessions
Interested in earning your MS from Viterbi?
How about starting an MS degree during your senior year?
The Viterbi Graduate Admission team is hosting a Progressive Degree information session!
What are the details?
When: Tuesday, September 5 at 5:00pm
Where: RTH 211
Who should attend?
All undergraduate students thinking about pursuing an MS degree through USC.
What is the Progressive Degree Program?
The Progressive Degree Program (PDP) gives continuing USC undergraduates another path to earning a Master's degree from USC.
The main advantages to a Progressive Degree are:
1) Start graduate-level classes during your senior year
2) Reduce the units required for a Master's DegreeLocation: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Undergrad
Contact: Viterbi PDP
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Cookie Decorating with Alpha Omega Epsilon
Tue, Sep 05, 2017 @ 07:00 PM - 07:00 PM
Viterbi School of Engineering Student Organizations
Student Activity
Come and decorate cookies with the actives of Alpha Omega Epsilon while learning more about our sorority! This event is free :)
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 109
Audiences: Undergrad
Contact: Alpha Omega Epsilon USC
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