83 citations · 107 across the 6 of their papers we have counts for
6 papers
Masked Subspace Clustering Methods
Jiebo Song, Huaming Ling
To further utilize the unsupervised features and pairwise information, we propose a general Bilevel Clustering Optimization (BCO) framework to improve the performance of clustering…
Fast and Scalable Semi-Supervised Learning for Multi-View Subspace Clustering
Huaming Ling, Chenglong Bao, Jiebo Song +1
In this paper, we introduce a Fast and Scalable Semi-supervised Multi-view Subspace Clustering (FSSMSC) method, a novel solution to the high computational complexity commonly found…
PCNN: Pattern-based Fine-Grained Regular Pruning towards Optimizing CNN Accelerators
Zhanhong Tan, Jiebo Song, Xiaolong Ma +8
Weight pruning is a powerful technique to realize model compression. We propose PCNN, a fine-grained regular 1D pruning method. A novel index format called Sparsity Pattern Mask (S…
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation
Shaokai Ye, Kailu Wu, Mu Zhou +6
Existing domain adaptation methods aim at learning features that can be generalized among domains. These methods commonly require to update source classifier to adapt to the target…
SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models
Linfeng Zhang, Zhanhong Tan, Jiebo Song +3
Remarkable achievements have been attained by deep neural networks in various applications. However, the increasing depth and width of such models also lead to explosive growth in…
Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation
Linfeng Zhang, Jiebo Song, Anni Gao +3
Convolutional neural networks have been widely deployed in various application scenarios. In order to extend the applications' boundaries to some accuracy-crucial domains, research…