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Events for March 11, 2021
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CS Colloquium: Gedas Bertasius (Facebook AI) - Designing Video Models for Human Behavior Understanding
Thu, Mar 11, 2021 @ 09:00 AM - 10:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Gedas Bertasius, Facebook AI
Talk Title: Designing Video Models for Human Behavior Understanding
Series: CS Colloquium
Abstract: Many modern computer vision applications require extracting core attributes of human behavior such as attention, action, or intention. Extracting such behavioral attributes requires powerful video models that can reason about human behavior directly from raw video data. To design such models we need to answer the following three questions: how do we (1) model videos, (2) learn from videos, and lastly, (3) use videos to predict human behavior?
In this talk I will present a series of methods to answer each of these questions. First, I will introduce TimeSformer, the first convolution-free architecture for video modeling built exclusively with self-attention. It achieves the best reported numbers on major action recognition benchmarks while also being more efficient than state-of-the-art 3D CNNs. Afterwards, I will present COBE, a new large-scale framework for learning contextualized object representations in settings involving human-object interactions. Our approach exploits automatically-transcribed speech narrations from instructional YouTube videos, and it does not require manual annotations. Lastly, I will introduce a self-supervised learning approach for predicting a basketball player's future motion trajectory from an unlabeled collection of first-person basketball videos.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Gedas Bertasius is a postdoctoral researcher at Facebook AI working on computer vision and machine learning problems. His current research focuses on topics of video understanding, first-person vision, and multi-modal deep learning. He received his Bachelors Degree in Computer Science from Dartmouth College, and a Ph.D. in Computer Science from the University of Pennsylvania. His recent work was nominated for the CPVR 2020 best paper award.
Host: Ramakant Nevatia
Audiences: By invitation only.
Contact: Assistant to CS chair
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Virtual First-Year Admission Information SessionThu, Mar 11, 2021 @ 09:00 AM - 10:00 AM
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
Our virtual information session is a live presentation from a USC Viterbi admission counselor designed for high school students and their family members to learn more about the USC Viterbi undergraduate experience. Our session will cover an overview of our undergraduate engineering programs, the application process, and more on student life. Guests will be able to ask questions and engage in further discussion toward the end of the session.
Please Register Here!Audiences: Everyone Is Invited
Contact: Viterbi Admission
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CS Colloquium: Jiaming Song (Stanford University) - Beyond Function Approximation: Compression, Inference, and Generation via Supervised Learning
Thu, Mar 11, 2021 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Jiaming Song, Stanford University
Talk Title: Beyond Function Approximation: Compression, Inference, and Generation via Supervised Learning
Series: CS Colloquium
Abstract: Supervised learning methods have advanced considerably thanks to deep function approximators. However, important problems such as compression, probabilistic inference, and generative modeling cannot be directly addressed by supervised learning. At the core, these problems involve estimating (and optimizing) a suitable notion of distance between two probability distributions, which is challenging in high-dimensional spaces. In this talk, I will propose techniques to estimate and optimize divergences more effectively by leveraging advances in supervised learning. I will describe an algorithm for estimating mutual information that approaches a fundamental limit of all valid lower bound estimators and can empirically compress neural networks by up to 70% without losing accuracy. I will also show how these techniques can be used to accelerate probabilistic inference algorithms that have been developed for decades by nearly 10x, improve generative modeling and infer suitable rewards for sequential decision making.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Jiaming Song is a fifth-year Ph.D. candidate in the Computer Science Department at Stanford University, advised by Stefano Ermon. His research focuses on learning and inference algorithms for deep probabilistic models with applications in unsupervised representation learning, generative modeling, and inverse reinforcement learning. He received his B.Eng degree in Computer Science from Tsinghua University in 2016. He was a recipient of the Qualcomm Innovation Fellowship.
Host: Bistra Dilkina
Audiences: By invitation only.
Contact: Assistant to CS chair
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Undergraduate Advisement Drop-in Hours
Thu, Mar 11, 2021 @ 01:30 PM - 02:30 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
Do you have a quick question? The CS advisement team will be available for drop-in live chat advisement for declared undergraduate students in our four majors during the spring semester on Tuesdays, Wednesdays, and Thursdays from 1:30pm to 2:30pm Pacific Time. Access the live chat on our website at: https://www.cs.usc.edu/chat/
Location: Online
Audiences: Undergrad
Contact: USC Computer Science
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Sage Corps Summer Program Info Session: Intern with Global Startup
Thu, Mar 11, 2021 @ 03:00 PM - 04:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Join our Founder and CEO, Matt Meltzer for an info session to learn about Sage Corps' unique program that has helped over 900 top college students accelerate their career development. 93% of Sage Corps alumni land full-time jobs within 3 months of graduating from college.
In our program, you'll:
- Complete 50+ hours of professional skill training in a selected vertical (marketing, business development & analysis; UX/UI & graphic design; software development; data analytics)
- Intern with a global startup for 12 weeks this summer
- Attend professional networking events
- Connect with some of our 900+ alumni now at top global companies like Nike, Google, IBM, Accenture, and JP Morgan
Sage Corps accepts all majors and any year in school, as well as non-US citizens. All are welcome to attend our info session.
For more information about Sage Corps, visit www.sagecorps.com. For real-time updates about Sage Corps programs, job opportunities, and other relevant news, follow Sage Corps on Instagram (@sagecorps) or LinkedIn.
To RSVP: Viterbi Career Gateway > Events > Information SessionsAudiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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Career Conversations: How to Impress Employers
Thu, Mar 11, 2021 @ 04:00 PM - 04:30 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Will your skill set stand out to employers? Join our 2-part series of Career Conversations to gain an inside look at employer feedback for Viterbi students. During this session, learn practices to develop the key leadership and problem-solving skills employers want to see more of.
To access this workshop:
Log into Viterbi Career Gateway>> Events>>Workshops: https://shibboleth-viterbi-usc-csm.symplicity.com/sso/
For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.Location: Online
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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CS Colloquium: Swabha Swayamdipta (Allen Institute for AI) - Addressing Biases for Robust, Generalizable AI
Thu, Mar 11, 2021 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Swabha Swayamdipta, Allen Institute for AI
Talk Title: Addressing Biases for Robust, Generalizable AI
Series: CS Colloquium
Abstract: Artificial Intelligence has made unprecedented progress in the past decade. However, there still remains a large gap between the decision-making capabilities of humans and machines. In this talk, I will investigate two factors to explain why. First, I will discuss the presence of undesirable biases in datasets, which ultimately hurt generalization. I will then present bias mitigation algorithms that boost the ability of AI models to generalize to unseen data. Second, I will explore task-specific prior knowledge which aids robust generalization, but is often ignored when training modern AI architectures. Throughout this discussion, I will focus my attention on language applications, and will show how certain underlying structures can provide useful inductive biases for inferring meaning in natural language. I will conclude with a discussion of how the broader framework of dataset and model biases will play a critical role in the societal impact of AI, going forward.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Swabha Swayamdipta is a postdoctoral investigator at the Allen Institute for AI, working with Yejin Choi. Her research focuses on natural language processing, where she explores dataset and linguistic structural biases, and model interpretability. Swabha received her Ph.D. from Carnegie Mellon University, under the supervision of Noah A. Smith and Chris Dyer. During most of her Ph.D. she was a visiting student at the University of Washington. She holds a Masters degree from Columbia University, where she was advised by Owen Rambow. Her research has been published at leading NLP and machine learning conferences, and has received an honorable mention for the best paper at ACL 2020.
Host: Xiang Ren
Audiences: By invitation only.
Contact: Assistant to CS chair
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ACM Social Game Night
Thu, Mar 11, 2021 @ 07:00 PM - 08:00 PM
Thomas Lord Department of Computer Science
Student Activity
Stressed about midterms? Want to meet some of your classmates? Join ACM on Thursday, March 11, from 7-8 PM for our second social of the semester. We will be playing Codenames!
Find out if you have what it takes to be the ultimate -spymaster-.
Learn more at https://www.facebook.com/events/281047960107761/
Location: Online - Zoom
Audiences: Undergraduate and Graduate Students
Contact: ACM
