Research Seminars @ Illinois

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Tailored for undergraduate researchers, this calendar is a curated list of research seminars at the University of Illinois. Explore the diverse world of research and expand your knowledge through engaging sessions designed to inspire and enlighten.

To have your events added or removed from this calendar, please contact OUR at ugresearch@illinois.edu

COLLOQUIUM: Simon Du, "Pre-Training Data Selection for Representation Learning"

Event Type
Seminar/Symposium
Sponsor
Illinois Computer Science
Location
HYBRID: 2405 Siebel Center for Computer Science or online
Virtual
wifi event
Date
Feb 26, 2024   3:30 pm  
Views
299
Originating Calendar
Computer Science Colloquium Series

Zoom: https://illinois.zoom.us/j/86064910025?pwd=OUZSYkx1alpsbkl2Kys5MnZDZTljdz09

Refreshments Provided.

Abstract: 
Pre-training datasets are a critical component in recent breakthroughs in artificial intelligence. However, their design has not received the same level of research attention as model architectures or training algorithms. In this presentation, I will discuss our recent work on pre-training data selection for representation learning in the contexts of multi-modal contrastive learning and multi-task representation learning. For multi-modal contrastive learning, we propose a new notion, the Variance Alignment Score (VAS). We demonstrate that by maximizing the VAS as a data selection strategy, we can achieve superior performance on dataset selection benchmarks. For multi-task representation learning, we explore how to select the most relevant pre-training tasks for a target downstream task. We introduce a metric to characterize task relevance and design a new method for actively selecting the most pertinent tasks.

Bio:
Simon S. Du is an assistant professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. His research interests are broadly in machine learning, such as deep learning, representation learning, and reinforcement learning. Prior to starting as faculty, he was a postdoc at the Institute for Advanced Study. He completed his Ph.D. in Machine Learning at Carnegie Mellon University. Simon's research has been recognized by a Samsung AI Researcher of the Year Award, an NSF CAREER award, an Intel Rising Star Faculty Award, an Nvidia Pioneer Award, a AAAI New Faculty Highlights, a Distinguished Dissertation Award honorable mention from CMU, among others.


Part of the Illinois Computer Science Speakers Series. Faculty Host: Hanghang Tong


Meeting ID: 860 6491 0025 
Passcode: csillinois


If accommodation is required, please email <erink@illinois.edu> or <communications@cs.illinois.edu>. Someone from our staff will contact you to discuss your specific needs



 

 

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