17 citations · 52 across the 9 of their papers we have counts for
6 papers · 1 filter
On the quantization of recurrent neural networks
Jian Li, Raziel Alvarez
Integer quantization of neural networks can be defined as the approximation of the high precision computation of the canonical neural network formulation, using reduced integer pre…
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks
Kaifeng Lyu, Jian Li
In this paper, we study the implicit regularization of the gradient descent algorithm in homogeneous neural networks, including fully-connected and convolutional neural networks wi…
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning
Jian Li, Xuanyuan Luo, Mingda Qiao
Generalization error (also known as the out-of-sample error) measures how well the hypothesis learned from training data generalizes to previously unseen data. Proving tight genera…
Generative Adversarial Mapping Networks
Jianbo Guo, Guangxiang Zhu, Jian Li
Generative Adversarial Networks (GANs) have shown impressive performance in generating photo-realistic images. They fit generative models by minimizing certain distance measure bet…
Practical Algorithms for Best-K Identification in Multi-Armed Bandits
Haotian Jiang, Jian Li, Mingda Qiao
In the Best- identification problem (Best--Arm), we are given stochastic bandit arms with unknown reward distributions. Our goal is to identify the arms with the larg…
Nearly Instance Optimal Sample Complexity Bounds for Top-k Arm Selection
Lijie Chen, Jian Li, Mingda Qiao
In the Best--Arm problem, we are given stochastic bandit arms, each associated with an unknown reward distribution. We are required to identify the arms with the largest…