4 papers
Binary and Ternary Quantization Can Enhance Feature Discrimination
Weizhi Lu, Mingrui Chen, Weiyu Li
Quantization is widely applied in machine learning to reduce computational and storage costs for both data and models. Considering that classification tasks are fundamental to the…
Ternary and Binary Quantization for Improved Classification
Weizhi Lu, Mingrui Chen, Kai Guo +1
Dimension reduction and data quantization are two important methods for reducing data complexity. In the paper, we study the methodology of first reducing data dimension by random…
Cascaded Compressed Sensing Networks: A Reversible Architecture for Layerwise Learning
Weizhi Lu, Mingrui Chen, Kai Guo +1
Recently, the method that learns networks layer by layer has attracted increasing interest for its ease of analysis. For the method, the main challenge lies in deriving an optimiza…
Deep Learning to Ternary Hash Codes by Continuation
Mingrui Chen, Weiyu Li, Weizhi Lu
Recently, it has been observed that {0,1,-1}-ternary codes which are simply generated from deep features by hard thresholding, tend to outperform {-1,1}-binary codes in image retri…