1 code implementation • 3 Feb 2024 • Xinyu Peng, Ziyang Zheng, Wenrui Dai, Nuoqian Xiao, Chenglin Li, Junni Zou, Hongkai Xiong
To achieve posterior covariance optimization without retraining, we provide general plug-and-play solutions based on two approaches specifically designed for leveraging pre-trained models with and without reverse covariance.
no code implementations • 15 May 2021 • Xinyu Peng, Jiawei Zhang, Fei-Yue Wang, Li Li
As a promising tool to better understand the learning dynamic of minibatch SGD, the information bottleneck (IB) theory claims that the optimization process consists of an initial fitting phase and the following compression phase.
no code implementations • 11 Mar 2019 • Xinyu Peng, Li Li, Fei-Yue Wang
Machine learning, especially deep neural networks, has been rapidly developed in fields including computer vision, speech recognition and reinforcement learning.