Learning A Deep $\ell_\infty$ Encoder for Hashing

@inproceedings{Wang2016LearningAD,
  title={Learning A Deep \$\ell_\infty\$ Encoder for Hashing},
  author={Zhangyang Wang and Yingzhen Yang and Shiyu Chang and Qing Ling and Thomas S. Huang},
  year={2016}
}
We investigate the `∞-constrained representation which demonstrates robustness to quantization errors, utilizing the tool of deep learning. Based on the Alternating Direction Method of Multipliers (ADMM), we formulate the original convex minimization problem as a feed-forward neural network, named Deep `∞ Encoder, by introducing the novel Bounded Linear Unit (BLU) neuron and modeling the Lagrange multipliers as network biases. Such a structural prior acts as an effective network regularization… CONTINUE READING
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