51 citations · 190 across the 18 of their papers we have counts for
4 papers · 1 filter
Depthwise Convolution is All You Need for Learning Multiple Visual Domains
Yunhui Guo, Yandong Li, Rogerio Feris +2
There is a growing interest in designing models that can deal with images from different visual domains. If there exists a universal structure in different visual domains that can…
Learning to Adaptively Scale Recurrent Neural Networks
Hao Hu, Liqiang Wang, Guo-Jun Qi
Recent advancements in recurrent neural network (RNN) research have demonstrated the superiority of utilizing multiscale structures in learning temporal representations of time ser…
Asynchronous Delay-Aware Accelerated Proximal Coordinate Descent for Nonconvex Nonsmooth Problems
Ehsan Kazemi, Liqiang Wang
Nonconvex and nonsmooth problems have recently attracted considerable attention in machine learning. However, developing efficient methods for the nonconvex and nonsmooth optimizat…
AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data
Liheng Zhang, Guo-Jun Qi, Liqiang Wang +1
The success of deep neural networks often relies on a large amount of labeled examples, which can be difficult to obtain in many real scenarios. To address this challenge, unsuperv…