163 citations · 1.2k across the 128 of their papers we have counts for
11 papers · 1 filter
Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets
Mingrui Liu, Youssef Mroueh, Jerret Ross +4
Adaptive gradient algorithms perform gradient-based updates using the history of gradients and are ubiquitous in training deep neural networks. While adaptive gradient methods theo…
A Simple and Effective Framework for Pairwise Deep Metric Learning
Qi Qi, Yan Yan, Xiaoyu Wang +1
Deep metric learning (DML) has received much attention in deep learning due to its wide applications in computer vision. Previous studies have focused on designing complicated loss…
A Decentralized Parallel Algorithm for Training Generative Adversarial Nets
Mingrui Liu, Wei Zhang, Youssef Mroueh +4
Generative Adversarial Networks (GANs) are a powerful class of generative models in the deep learning community. Current practice on large-scale GAN training utilizes large models…
Improved Schemes for Episodic Memory-based Lifelong Learning
Yunhui Guo, Mingrui Liu, Tianbao Yang +1
Current deep neural networks can achieve remarkable performance on a single task. However, when the deep neural network is continually trained on a sequence of tasks, it seems to g…
Stochastic AUC Maximization with Deep Neural Networks
Mingrui Liu, Zhuoning Yuan, Yiming Ying +1
Stochastic AUC maximization has garnered an increasing interest due to better fit to imbalanced data classification. However, existing works are limited to stochastic AUC maximizat…
Stochastic Optimization for Non-convex Inf-Projection Problems
Yan Yan, Yi Xu, Lijun Zhang +2
In this paper, we study a family of non-convex and possibly non-smooth inf-projection minimization problems, where the target objective function is equal to minimization of a joint…