165 citations · 555 across the 19 of their papers we have counts for
6 papers · 1 filter
Towards Accurate and Compact Architectures via Neural Architecture Transformer
Yong Guo, Yin Zheng, Mingkui Tan +5
Designing effective architectures is one of the key factors behind the success of deep neural networks. Existing deep architectures are either manually designed or automatically se…
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search
Yong Guo, Yaofo Chen, Yin Zheng +4
Neural architecture search (NAS) has become an important approach to automatically find effective architectures. To cover all possible good architectures, we need to search in an e…
Fast Single Image Reflection Suppression via Convex Optimization
Yang Yang, Wenye Ma, Yin Zheng +2
Removing undesired reflections from images taken through the glass is of great importance in computer vision. It serves as a means to enhance the image quality for aesthetic purpos…
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
Zhuxi Jiang, Yin Zheng, Huachun Tan +2
Clustering is among the most fundamental tasks in computer vision and machine learning. In this paper, we propose Variational Deep Embedding (VaDE), a novel unsupervised generative…
A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data
Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to deal with multimodal data, such as in image annotation tasks. Another popular approach t…
A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation
Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to perform scene recognition and annotation. Recently, a new type of topic model called the…