no code implementations • 30 May 2023 • Zhenyu Zhu, Fanghui Liu, Grigorios G Chrysos, Francesco Locatello, Volkan Cevher
This paper focuses on over-parameterized deep neural networks (DNNs) with ReLU activation functions and proves that when the data distribution is well-separated, DNNs can achieve Bayes-optimal test error for classification while obtaining (nearly) zero-training error under the lazy training regime.
no code implementations • 16 Sep 2022 • Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios G Chrysos, Volkan Cevher
Neural tangent kernel (NTK) is a powerful tool to analyze training dynamics of neural networks and their generalization bounds.
no code implementations • 15 Sep 2022 • Zhenyu Zhu, Fanghui Liu, Grigorios G Chrysos, Volkan Cevher
In particular, when initialized with LeCun initialization, depth helps robustness with the lazy training regime.
no code implementations • 15 Sep 2022 • Zhenyu Zhu, Fanghui Liu, Grigorios G Chrysos, Volkan Cevher
To this end, we derive the lower (and upper) bounds of the minimum eigenvalue of the Neural Tangent Kernel (NTK) under the (in)finite-width regime using a certain search space including mixed activation functions, fully connected, and residual neural networks.
no code implementations • ICLR 2022 • Zhenyu Zhu, Fabian Latorre, Grigorios G Chrysos, Volkan Cevher
While the class of Polynomial Nets demonstrates comparable performance to neural networks (NN), it currently has neither theoretical generalization characterization nor robustness guarantees.
no code implementations • 15 Feb 2021 • Zhenyu Zhu, Luciano Rezzolla
The hypothesis that strange quark matter is the true ground state of matter has been investigated for almost four decades, but only a few works have explored the dynamics of binary systems of quark stars.
High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology
no code implementations • 6 May 2020 • Zhenyu Zhu, Ang Li, Luciano Rezzolla
Hence, the measurement of these corrections has the potential of providing important information on the equation of state of nuclear matter.
High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology
no code implementations • 3 Sep 2019 • Guoqing Li, Meng Zhang, Qianru Zhang, Ziyang Chen, Wenzhao Liu, Jiaojie Li, Xuzhao Shen, Jianjun Li, Zhenyu Zhu, Chau Yuen
To design more efficient lightweight concolutional neural netwok, Depthwise-Pointwise-Depthwise inverted bottleneck block (DPD block) is proposed and DPDNet is designed by stacking DPD block.