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Events for the 5th week of February
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CS Colloquium: Michael Everett (MIT) - Fully Autonomous Robot Navigation in Human Environments
Mon, Feb 24, 2020 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Michael Everett, MIT
Talk Title: Fully Autonomous Robot Navigation in Human Environments
Series: CS Colloquium
Abstract: Today's robots are still quite limited in their ability to process information about multiple other objects in order to plan safe and efficient motions through previously unseen environments. Major technical challenges are currently sidestepped by restrictive engineering solutions (e.g., preventing humans from working alongside factory robots, collecting detailed prior maps in every intended operating environment). This talk will present frameworks that enable long-term autonomy for robots embedded among pedestrians and context-guided exploration in new environments. Furthermore, it will discuss future research directions toward safely training and deploying robots in our society.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Michael Everett is a final-year PhD Candidate at MIT working with Prof. Jonathan How. He received the SM degree (2017) and the SB degree (2015) from MIT in Mechanical Engineering. His research addresses fundamental gaps in the connection of machine learning and real mobile robotics, with recent emphasis on developing the theory of safety/robustness of learned modules. His works have won the Best Paper Award on Cognitive Robotics at IROS 2019, the Best Student Paper Award and finalist for the Best Paper Award on Cognitive Robotics at IROS 2017, and finalist for the Best Multi-Robot Systems Paper Award at ICRA 2017. He has been interviewed live on the air by BBC Radio and his robots were featured by Today Show, Reuters, and the Boston Globe.
Host: Nora Ayanian
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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ByteDance Trojan Talk
Mon, Feb 24, 2020 @ 07:00 PM - 09:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
ByteDance is hiring at USC Viterbi! During the presentation you are expected to learn about our corporate culture, technology, growth path, positions, etc.
Target group:
- Full-Time: Class of 2020 graduates (Graduation timeï¼2019.9-2020.8ï¼
- Summer internï¼Class of 2021 graduates (Graduation timeï¼after 2020.8ï½ï¼
Working location: Mountain View, Los Angeles, Beijing, Shanghai, Singapore, etc.
ByteDance is one of the first companies to launch mobile-first products powered by smart recommendation technology and we are aiming to build the best Global Creation and Interaction Platform. Come to join us, Inspire Creativity, Enrich Life!Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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CS Colloquium: Robin Jia (Stanford University) - Building Robust Natural Language Processing Systems
Tue, Feb 25, 2020 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Robin Jia, Stanford University
Talk Title: Building Robust Natural Language Processing Systems
Series: CS Colloquium
Abstract: While modern NLP systems have achieved outstanding performance on static benchmarks, they often fail catastrophically when presented with inputs from different sources or inputs that have been adversarial perturbed. This lack of robustness exposes troubling gaps in current models' understanding capabilities, and poses challenges for deployment of NLP systems in high-stakes situations. In this talk, I will demonstrate that building robust NLP systems requires reexamining all aspects of the current model building paradigm. First, I will show that adversarially constructed test data reveals vulnerabilities that are left unexposed by standard evaluation methods. Second, I will demonstrate that active learning, in which data is adaptively collected based on a model's current predictions, can significantly improve the ability of models to generalize robustly, compared to the use of static training datasets. Finally, I will show how to train NLP models to produce certificates of robustness---guarantees that for a given example and combinatorially large class of possible perturbations, no perturbation can cause a misclassification.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Robin Jia is a sixth-year Ph.D. student at Stanford University advised by Percy Liang. His research interests lie broadly in building natural language processing systems that can generalize to unexpected test-time inputs. Robin's work has received an Outstanding Paper Award at EMNLP 2017 and a Best Short Paper Award at ACL 2018. He has been supported by an NSF Graduate Research Fellowship.
Host: Xiang Ren
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Job Offer and Salary Negotiation Workshop
Tue, Feb 25, 2020 @ 12:00 PM - 01:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Considering multiple internship/job offers? Want to negotiate your salary?
Viterbi students and alumni are in-demand, and many of you receive multiple competing offers for internships and full-time jobs. But what do you do when you have already accepted an offer and then get one from your dream company? How do you leverage your offers to negotiate a better salary or increased benefits? Attend our upcoming Job Offer & Salary Negotiation workshop to get guidance on the process.
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: All Viterbi Students
Contact: RTH 218 Viterbi Career Connections
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Job Offer and Salary Negotiation Workshop
Tue, Feb 25, 2020 @ 12:00 PM - 01:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Considering multiple internship/job offers? Want to negotiate your salary?
Viterbi students and alumni are in-demand, and many of you receive multiple competing offers for internships and full-time jobs. But what do you do when you have already accepted an offer and then get one from your dream company? How do you leverage your offers to negotiate a better salary or increased benefits? Attend our upcoming Job Offer & Salary Negotiation workshop to get guidance on the process.
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: All Viterbi Students
Contact: RTH 218 Viterbi Career Connections
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VIP Reflection Session
Tue, Feb 25, 2020 @ 01:00 PM - 02:00 PM
Viterbi School of Engineering Student Affairs
Receptions & Special Events
Monthly reflection sessions for students to come together and give meaning to their experiences.
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Undergrad
Contact: Viterbi Undergraduate Programs
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ECE Seminar
Tue, Feb 25, 2020 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Junsong Yuan, PhD, State University of New York
Talk Title: Beyond Deep Recognition: Discovering Visual Patterns in Big Visual Data
Abstract: Thanks to the success of deep learning, many computer vision tasks nowadays are formulated as regression problems. However, often times one has to rely on large amounts of annotated training data to make the high-dimensional regression successful. In this talk, we will discuss a complementary yet overlooked problem beyond deep visual recognition and regression. We will discuss why and how to discover visual patterns in images and videos that are not annotated, e.g., unsupervised and weakly-supervised visual learning and pattern discovery, and explore how to utilize them to better model, search, and interpret big visual data. Applications in visual search, object detection, action recognition, and video analytics will also be discussed.
Biography: Junsong Yuan is an Associate Professor and Director of Visual Computing Lab of CSE Department, State University of New York at Buffalo. Before that he was an Associate Professor at Nanyang Technological University (NTU), Singapore. He received his PhD from Northwestern University and M.Eng. from National University of Singapore. He is currently Associate Editor of IEEE Trans. on Image Processing (T-IP) and Machine Vision and Applications (MVA), and Senior Area Editor of Journal of Visual Communication and Image Representation (JVCI), and served as program co-chair for ICME 2018 and area chair for CVPR/ACM MM/WACV/ACCV/ICIP/ICPR etc. He received Best Paper Award from IEEE Trans. on Multimedia, Nanyang Assistant Professorship from NTU, and Outstanding EECS Ph.D. Thesis award from Northwestern University. He is a Fellow of International Association of Pattern Recognition (IAPR).
Host: Dr. C.-C. Jay Kuo
More Information: Yunsong Yuan Seminar 2.25.20.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gloria Halfacre
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ISE 651 - Epstein Seminar
Tue, Feb 25, 2020 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Daniel Kuhn, Chair, Risk Analytics and Optimization - The Ecole Polytechnique Fédérale de Lausanne (EPFL)
Talk Title: Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning
Host: Dr. Phebe Vayanos
More Information: February 25, 2020.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Grace Owh
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Trojan Talk - LegalZoom
Tue, Feb 25, 2020 @ 06:00 PM - 08:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Presentation about LegalZoom and the Data Analytics function.
LegalZoom currently has job opportunities available within the Data Analytics' team, so we would like to share information as to our organization, culture, and how the Analytics function plays a key role in understanding our customers with insights and assist in key business decisions.
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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Computer Science General Faculty Meeting
Wed, Feb 26, 2020 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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AME Seminar
Wed, Feb 26, 2020 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Garrett Reisman, USC
Talk Title: Human Spaceflight-“Recent Past, Near Future and Educational Activities at Viterbi
Abstract: The presentation will highlight his personal experiences flying on the Space Shuttle and the International Space Station while serving as a NASA Astronaut from 1998 to 2011. After describing these unique experiences he will discuss his transition to SpaceX and the state of the commercial human spaceflight industry. Finally, the human spaceflight graduate coursework which has recently been established in Viterbi ASTE department will be presented.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Location: 159
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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CS Colloquium: Minjoon Seo (University of Washington) - Web-Scale Neural Memory towards Universal Knowledge Interface
Thu, Feb 27, 2020 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Minjoon Seo, University of Washington
Talk Title: Web-scale Neural Memory towards Universal Knowledge Interface
Series: CS Colloquium
Abstract: Modern natural language tasks are increasingly dependent on external world knowledge. My PhD study has particularly focused on three challenges in this literature: handling unstructured knowledge, being scalable, and reasoning over knowledge data. I will mainly discuss my recent and on-going work on a web-scale neural memory that tackles all of the three challenges, and show how it serves as an effective interface for interacting with the world knowledge. I will conclude with an argument that designing a seamless and universal knowledge interface is a crucial research goal that can better address knowledge-dependency problem in machine learning tasks.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Minjoon Seo is a final-year Ph.D. student in the Allen School of Computer Science & Engineering at the University of Washington, advised by Hannaneh Hajishirzi and Ali Farhadi. His research interest has been mostly in the learning model for the extraction of (IE), the access to (QA), and the interplay of (Reasoning) knowledge in various forms of language data. He is supported by Facebook Fellowship and AI2 Key Scientific Challenges Award. He co-organizes the Workshop on Machine Reading for Question Answering (MRQA) and the Workshop on Representation Learning for NLP (RepL4NLP).
Host: Xiang Ren
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Tabling | Civil Engineering | Bachelors & Masters
Thu, Feb 27, 2020 @ 12:00 PM - 04:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Tabling Session - For future engineers
Los Angeles County is hiring Civil Engineering Assistants and Civil Engineering Students! Recruiting for bachelors and masters Civil Engineering students.
Stop by the Engineering Quad to learn more about both opportunities, drop your resume, and chat with recruiters. Stop by anytime between 12 pm and 4 pm.
Start your engineering journey at Public Works and enjoy a rewarding career in public service. As an LA County engineer, you will have an opportunity to join a dynamic team and play a meaningful role in enriching the lives of the 10 million residents we serve.
Location: E-Quad
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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ECE-EP Seminar - Maiken Mikkelsen, Thursday, February 27th at 2pm in EEB 132
Thu, Feb 27, 2020 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Maiken Mikkelsen, Duke University
Talk Title: Atomic-scale Engineering for On-chip Photonic Devices
Abstract: Nano- and quantum materials with unique optical properties hold the potential for breakthroughs in a wide range of areas from ultrafast optoelectronics and on-chip components for quantum information science to improve bio-sensing. An exciting opportunity to realize such new materials lies in controlling the local electromagnetic environment on the atomic- and molecular-scale (~1-10 nm), which enables extreme local field enhancements and drastically modified local density of states. We use creative nanofabrication techniques at the interface between chemistry and physics to realize this new regime together with ultrafast optical techniques to probe the emerging phenomena. Here, I will provide an overview of our recent research where we sculpt the electromagnetic fields on the atomic scale to realize ultrafast single photon sources, high-speed thermal photodetectors with on-chip spectral filters and metasurface-enhanced biosensors.
Biography: Maiken H. Mikkelsen is the James N. and Elizabeth H. Barton Associate Professor at Duke University in the Department of Electrical & Computer Engineering, and by courtesy, in the Departments of Physics and Mechanical Engineering & Materials Science. She received her B.S. in Physics from the University of Copenhagen in 2004, her Ph.D. in Physics from the University of California, Santa Barbara in 2009 and was a postdoctoral fellow at the University of California, Berkeley before joining Duke University in 2012. Her research explores nanophotonics and new quantum materials to enable transformative breakthroughs for optoelectronics, quantum science, the environment and human health. Her awards include the Maria Goeppert Mayer Award from the American Physical Society, the NSF CAREER award, the Moore Inventor Fellow award from the Gordon and Betty Moore Foundation, Young Investigator Program Awards from the Office of Naval Research, the Army Research Office and the Air Force Office of Scientific Research, the Cottrell Scholar Award from the Research Corporation for Science Advancement, the Early Career Achievement Award from SPIE - the International Society for Optics and Photonics, and is the recipient of an RO1 award from the National Institute of Health.
Host: ECE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
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VIP Lecture Series 1
Thu, Feb 27, 2020 @ 03:00 PM - 04:00 PM
Viterbi School of Engineering Student Affairs
Conferences, Lectures, & Seminars
Speaker: DJ Kast, STEM PROGRAMS -JEP
Abstract: VIP Guest Speaker - DJ Kast (STEM PROGRAMS -JEP)
USC Faculty, staff, and community members discuss the societal impacts of engineering. Also, volunteer opportunities will be discussed.
Host: Viterbi Impact Program
Location: Ronald Tutor Hall of Engineering (RTH) - 306
Audiences: Undergrad
Contact: Viterbi Undergraduate Programs
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Sonny Astani Civil and Environmental Engineering Seminar
Thu, Feb 27, 2020 @ 04:00 PM - 05:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Emily Grubert, Ph.D., Georgia Tech
Talk Title: Conventional Hydroelectricity and the Energy Transition
Abstract: See attached Abstract and Bio.
Host: Dr. Kelly Sanders
More Information: E. Grubert Abstract_ 02-27-2020.pdf
Location: Michelson Center for Convergent Bioscience (MCB) - 102
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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IISE Western Regional Conference
Fri, Feb 28, 2020
Daniel J. Epstein Department of Industrial and Systems Engineering, USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Various, Various
Talk Title: IISE Western Regional Conference
Abstract: The Institute of Industrial and Systems Engineers at the University of Southern California is hosting the 2020 IISE Western Regional Conference February 28 - March 1, 2020.
Please register here: https://ise.usc.edu/iise-student-conference
This conference is a unique opportunity for students and professionals in the field of Industrial Engineering to network, explore industry trends, and compete for a chance to present their work at the IISE Annual Conference and Expo 2020 in New Orleans, Louisiana.
The conference will be held on the main campus and includes the technical paper competition, keynote speakers, expert panels, plant tours, and other activities.
Host: Daniel J. Epstein Department of Industrial and Systems Engineering
More Info: https://ise.usc.edu/iise-student-conference/
More Information: ConferenceFlyer.pdf
Audiences: Everyone Is Invited
Contact: Greta Harrison
Event Link: https://ise.usc.edu/iise-student-conference/
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Grammar Tutoring
Fri, Feb 28, 2020 @ 10:00 AM - 12:00 PM
Viterbi School of Engineering Student Affairs
Workshops & Infosessions
INDIVIDUAL GRAMMAR TUTORIALS
Need help refining your grammar skills in your academic and professional writing? Meet one-on-one with professors from the Engineering Writing Program, work together on your grammar skills, and take your writing to the next level!
ALL VITERBI UNDERGRADUATE AND GRADUATE STUDENTS WELCOME!
Sign up here: http://bit.ly/grammaratUSC
All sessions will be via Zoom.
Questions? Contact helenhch@usc.eduLocation: ZOOM
Audiences: Graduate and Undergraduate Students
Contact: Helen Choi
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Machine Learning for Performance and Power Modeling/Prediction
Fri, Feb 28, 2020 @ 10:30 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. Lizy Kurian John, UT Austin
Talk Title: Machine Learning for Performance and Power Modeling/Prediction
Abstract: Estimating the power and thermal characteristics of SoCs is essential for designing its power delivery system, packaging, cooling, and power/thermal management schemes. Power models that estimate the power consumption of each functional unit/hardware component from first principles are slow and tedious to build. Machine learning can be used to create power models that are fast and reasonably accurate. Machine learning can also be used to calibrate analytical models that estimate power. In this talk, I will present some examples of performance and power modeling using machine learning.
Another application for machine learning has been to create max power stressmarks. Manually developing and tuning so called stressmarks is extremely tedious and time-consuming while requiring an intimate understanding of the processor. In our past research, we created a framework that uses machine learning for the automated generation of stressmarks. In this talk, the methodology of the creation of automatic stressmarks will be explained. Experiments on multiple platforms validating the proposed approach will be described.
Yet another application for machine learning is in cross-platform performance and power prediction. If one model is slow to run real-world benchmarks/workloads, is it possible to predict/estimate the performance/power by using runs on another platform? Are there correlations that can be exploited using machine learning to make cross-platform performance and power predictions? A methodology to perform cross-platform performance/power predictions will be presented in this talk.
Biography: Lizy Kurian John is Cullen Trust for Higher Education Endowed Professor in the Electrical and Computer Engineering at the University of Texas at Austin. She received her Ph. D in Computer Engineering from Pennsylvania State University. Her research interests include workload characterization, performance evaluation, memory systems, reconfigurable architectures, and high-performance architectures for emerging workloads. She is a recipient of many awards including The Pennsylvania State University Outstanding Engineering Alumnus 2011, the NSF CAREER award, UT Austin Engineering Foundation Faculty Award, Halliburton, Brown and Root Engineering Foundation Young Faculty Award 2001, University of Texas Alumni Association (Texas Exes) Teaching Award 2004, etc. She has co-authored books on Digital Systems Design using VHDL (Cengage Publishers, 2007, 2017), a book on Digital Systems Design using Verilog (Cengage Publishers, 2014) and has edited 4 books including a book on Computer Performance Evaluation and Benchmarking. In the past, she has served as Associate Editor of IEEE Transactions on Computers, IEEE Transactions on VLSI, IEEE Computer Architecture Letters, ACM Transactions on Architecture and Code Optimization, and IEEE Micro. She is currently the Editor-in-Chief of IEEE Micro. She holds 12 US patents and is an IEEE Fellow (Class of 2009).
Host: Xuehai Qian, xuehai.qian@usc.edu
More Information: 200228_Lizy John_CENG.pdf
Location: Ronald Tutor Hall of Engineering (RTH) - 105
Audiences: Everyone Is Invited
Contact: Brienne Moore
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Virtual Graduate Mixer
Fri, Feb 28, 2020 @ 01:00 PM - 05:00 PM
Viterbi School of Engineering Alumni
Receptions & Special Events
Don't miss out on this chance to chat with participants from all around the world! Share your experiences, exchange career tips and build your professional network -- all online, from any device.
Current Viterbi Students, Viterbi Alumni, Engineering Professionals, and Employers hiring Engineers are all encouraged to attend. Don't wait, register now!WebCast Link: Please register for more information.
Audiences: Everyone Is Invited
Contact: Kristy Ly
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PhD Defense - Ayush Jaiswal
Fri, Feb 28, 2020 @ 01:30 PM - 03:30 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Ayush Jaiswal
Date: Friday, February 28, 2020
Time: 1:30 PM - 3:30 PM
Location: SAL 213
Committee: Premkumar Natarajan (Chair), Ram Nevatia, Cauligi S. Raghavendra
Title: Invariant Representation Learning for Robust and Fair Predictions
Abstract:
Learning representations that are invariant to nuisance factors of data improves robustness of machine learning models, and promotes fairness for factors that represent biasing information. This view of invariance has been adopted for deep neural networks (DNNs) recently as they learn latent representations of data by design. Numerous methods for invariant representation learning for DNNs have emerged in recent literature, but the research problem remains challenging to solve: existing methods achieve partial invariance or fall short of optimal performance on the prediction tasks that the DNNs need to be trained for.
This thesis presents novel approaches for inducing invariant representations in DNNs by effectively separating predictive factors of data from undesired nuisances and biases. The presented methods improve the predictive performance and the fairness of DNNs through increased invariance to undesired factors. Empirical evaluation on a diverse collection of benchmark datasets shows that the presented methods achieve state-of-the-art performance.
Application of the invariance methods to real-world problems is also presented, demonstrating their practical utility. Specifically, the presented methods improve nuisance-robustness in presentation attack detection and automated speech recognition, fairness in face-based analytics, and generalization in low-data and semi-supervised learning settings.
Location: Henry Salvatori Computer Science Center (SAL) - 213
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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IISE Regional Conference
Sat, Feb 29, 2020
Viterbi School of Engineering Student Affairs
Conferences, Lectures, & Seminars
Speaker: ,
Talk Title:
Host:
Audiences: Everyone Is Invited
Contact: Viterbi Undergraduate Programs