Zhehao Huang
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    • Bi-LoRA: Efficient Sharpness-Aware Minimization for Fine-Tuning Large-Scale Models
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    • A Unified Gradient-based Framework for Task-agnostic Continual Learning-Unlearning
    • 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
    • Remaining-data-free 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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    • 🎉 Our paper "Towards Natural Machine Unlearning" is accepted by TPAMI
    • 🎉 Our paper "Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks" is accepted by ICLR 2025
    • 🎉 Our paper "Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement" is accepted by NeurIPS 2024 as Spotlight
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PyTorch

Oct 26, 2023 · 1 min read
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PyTorch is a Python package that provides tensor computation (like NumPy) with strong GPU acceleration.

Last updated on Oct 26, 2023
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Zhehao Huang
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Zhehao Huang
Ph.D. Student
Semanticscholar Streamline Icon: https://streamlinehq.comSemantic Scholar
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