Zhehao Huang
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    • Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks
    • Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
    • Online Continual Learning via Logit Adjusted Softmax
    • Towards Natural Machine Unlearning
    • Machine Unlearning by Suppressing Sample Contribution
    • Query Attack by Multi-Identity Surrogates
    • Trainable Weight Averaging: Efficient Training by Optimizing Historical Solutions
    • Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks
    • Low Dimensional Trajectory Hypothesis is True: DNNs Can Be Trained in Tiny Subspaces
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    • ๐ŸŽ‰ Our paper "Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks" is accepted by ICLR 2025
    • ๐ŸŽ‰ Our paper "Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement" is accepted by NeurIPS 2024 as Spotlight
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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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Zhehao Huang
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Zhehao Huang
PhD Student

← PyTorch Oct 26, 2023

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

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