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Events for February 03, 2025
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CS Colloquium: Justin Solomon (MIT) - Navigating, Restructuring and Reshaping Learned Latent Spaces
Mon, Feb 03, 2025 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Justin Solomon, MIT
Talk Title: Navigating, Restructuring and Reshaping Learned Latent Spaces
Abstract: Modern machine learning architectures often embed their inputs into a lower-dimensional latent space before generating a final output. A vast set of empirical results---and some emerging theory---predicts that these lower-dimensional codes often are highly structured, capturing lower-dimensional variation in the data. Based on this observation, in this talk I will describe efforts in my group to develop lightweight algorithms that navigate, restructure, and reshape learned latent spaces. Along the way, I will consider a variety of practical problems in machine learning, including low-rank adaptation of large models, regularization to promote local latent structure, and efficient training/evaluation of generative models. This talk will cover collaborative research with Rickard Gabrielsson, Kimia Nadjahi, Chris Scarvelis, Tal Shnitzer, Mikhail Yurochkin, Jiacheng Zhu, and others.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Justin Solomon is an Associate Professor of Electrical Engineering and Computer Science at MIT. He leads the Geometric Data Processing Group in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), which studies problems at the intersection of geometry, large-scale optimization, and applications.
Host: Yue Wang
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone (USC) is invited
Contact: CS Faculty Affairs
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
PhD Thesis Proposal - Tingting Tang
Mon, Feb 03, 2025 @ 12:30 PM - 01:30 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Optimizing Privacy-Preserving Machine Learning for Improved Privacy, Utility, and Efficiency Tradeoffs
Location: EEB 349
Date and Time: February 3, 2025, 12.30 PM-1.30 PM
Zoom Link: https://usc.zoom.us/j/7995244109?pwd=OUp6RWhUZlFGclgyN3hkREh0Z21ldz09
Committee: Murali Annavaram (Chair), Salman Avestimehr, Bhaskar Krishnamachari, Harsha Madhyastha, Sai Praneeth Karimireddy
Abstract: Privacy-preserving machine learning (PPML) is essential for protecting sensitive data in machine-learning applications, requiring a careful balance between privacy, utility, and efficiency. However, the trade-offs and interdependencies among these dimensions present significant design challenges. This thesis proposal explores and optimizes their interplay through low-rank decomposition, focusing on two key PPML technologies: Differential Privacy (DP) and Secure Multiparty Computation (MPC). In the context of DP-based graph neural networks (GNNs), I propose a novel training framework leveraging low-rank singular value perturbation to protect sensitive graph edges while preserving the primary graph structure. This approach achieves a significantly improved privacy-utility trade-off and demonstrates resilience to edge inference attacks. For MPC-based secure model inference, I propose leveraging low-rank decomposition for the linear layers of ML models, reducing the number of MPC multiplications required during offline and online phases. Techniques such as truncation skipping and linear layer concatenation further reduce computational and communication overheads, enhancing overall efficiency in MPC ML workflows without compromising the robust security guarantees provided by MPC. By addressing the interactions between privacy, utility, and efficiency, my proposal lays the foundation for more practical and effective deployment of privacy-preserving machine learning solutions in real-world applications.Location: Hughes Aircraft Electrical Engineering Center (EEB) - 349
Audiences: Everyone Is Invited
Contact: Tingting Tang
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
