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Welcome to the website of the <u>**L**</u>earning and <u>**IN**</u>ference <u>**S**</u>ystems (LINs) Lab at Westlake University!
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Our research interests lie in the intersection of optimization and generalization for deep learning:
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- leveraging theoretical/empirical understanding (e.g., loss landscape, and training dynamics)
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- to design efficient & robust methods (both learning and inference)
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- for deep learning (centralized) and collaborative deep learning (distributed and/or decentralized),
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- under imperfect environments (e.g., noisy, heterogeneous, and hardware-constrained).
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Welcome to the website of the <u>**L**</u>earning and <u>**IN**</u>ference <u>**S**</u>ystems (LINs) Lab at Westlake University!
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Our research interests lie in the intersection of optimization and generalization for deep learning:
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- leveraging theoretical/empirical understanding (e.g., loss landscape, and training dynamics)
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- to design efficient & robust methods (both learning and inference)
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- for deep learning (centralized) and collaborative deep learning (distributed and/or decentralized),
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- under imperfect environments (e.g., noisy, heterogeneous, and hardware-constrained).
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Check our [lab page](https://lins-lab.github.io/) and [github](https://lins-lab/)!
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