Jingwen Shi
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    • ๐ŸŽ‰ Thrilled to Share that Iโ€™ve Joined the Honor Society of Phi Kappa Phi!
    • ๐ŸŽ‰ Selected for the Harvard SEAS Research and Academic Exchange Program
    • ๐ŸŽ‰ Initiating the Process for a Long-Term Collaboration with AT&T Labs
    • ๐ŸŽ‰ Our Mobicom '22 paper has been selected for the SIGMOBILE Research Highlights!
    • ๐ŸŽ‰ Our 5G/4G IMS security paper is accepted by ACM MobiCom'24!
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    • Securing Multimedia Services In Next-Generation Mobile Systems - From Devices To Infrastructure
    • Detect the Undetected - An AI-Assisted Framework for Traffic Clustering and Anomaly Detection
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    • CSE825 Computer and Network Security
    • CSE425 Intro to Computer Security
    • CSE476 Mobile Application Development
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    • IMS is Not That Secure on Your 5G/4G Phones
    • Taming the Insecurity of Cellular Emergency Services (9โ€“1-1): From Vulnerabilities to Secure Designs
    • When Good Turns Evil: Encrypted 5G/4G Voice Calls Can Leak Your Identities
    • Handling Data Heterogeneity in Federated Learning via Knowledge Fusion
    • Uncovering insecure designs of cellular emergency services (911)
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scikit-learn

Oct 26, 2023 ยท 1 min read
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scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.

Last updated on Oct 26, 2023
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Jingwen Shi
Authors
Jingwen Shi
Ph.D. Candidate

← PyTorch Oct 26, 2023

ยฉ 2025 Jingwen Shi. This work is licensed under CC BY NC ND 4.0

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