4 citations · 5 across the 3 of their papers we have counts for
4 papers
AGD: an Auto-switchable Optimizer using Stepwise Gradient Difference for Preconditioning Matrix
Yun Yue, Zhiling Ye, Jiadi Jiang +2
Adaptive optimizers, such as Adam, have achieved remarkable success in deep learning. A key component of these optimizers is the so-called preconditioning matrix, providing enhance…
Sharpness-Aware Minimization Revisited: Weighted Sharpness as a Regularization Term
Yun Yue, Jiadi Jiang, Zhiling Ye +3
Deep Neural Networks (DNNs) generalization is known to be closely related to the flatness of minima, leading to the development of Sharpness-Aware Minimization (SAM) for seeking fl…
Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction
Yun Yue, Yongchao Liu, Suo Tong +7
We develop a novel framework that adds the regularizers of the sparse group lasso to a family of adaptive optimizers in deep learning, such as Momentum, Adagrad, Adam, AMSGrad, Ada…
A Generalized and Robust Method Towards Practical Gaze Estimation on Smart Phone
Tianchu Guo, Yongchao Liu, Hui Zhang +5
Gaze estimation for ordinary smart phone, e.g. estimating where the user is looking at on the phone screen, can be applied in various applications. However, the widely used appeara…