Jiun Tian Hoe, Kam Woh Ng, Tianyu Zhang, Chee Seng Chan, Yi-Zhe Song, Tao Xiang. One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 24286-24298, 2021. [doi]
@inproceedings{HoeNZCSX21,
title = {One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective},
author = {Jiun Tian Hoe and Kam Woh Ng and Tianyu Zhang and Chee Seng Chan and Yi-Zhe Song and Tao Xiang},
year = {2021},
url = {https://proceedings.neurips.cc/paper/2021/hash/cbcb58ac2e496207586df2854b17995f-Abstract.html},
researchr = {https://researchr.org/publication/HoeNZCSX21},
cites = {0},
citedby = {0},
pages = {24286-24298},
booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}