Matrix Factorization with Scale-Invariant Parameters

Zeng, Guangxiang; Zhu, Hengshu; Liu, Qi; Luo, Ping; Chen, Enhong; Zhang, Tong

Matrix Factorization with Scale-Invariant Parameters

Guangxiang Zeng, Hengshu Zhu, Qi Liu, Ping Luo, Enhong Chen, Tong Zhang

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Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Special Track on Machine Learning. Pages 4017-4023.

Abstract

Tuning hyper-parameters for large-scale matrix factorization (MF) is very time consuming and sometimes unacceptable. Intuitively, we want to tune hyper-parameters on small sub-matrix sample and then exploit them into the original large-scale matrix. However, most of existing MF methods are scale-variant, which means the optimal hyper-parameters usually change with the different scale of matrices. To this end, in this paper we propose a scale-invariant parametric MF method, where a set of scale-invariant parameters is defined for model complexity regularization. Therefore, the proposed method can free us from tuning hyper-parameters on large-scale matrix, and achieve a good performance in a more efficient way. Extensive experiments on real-world dataset clearly validate both the effectiveness and efficiency of our method.

Guangxiang Zeng, Hengshu Zhu, Qi Liu, Ping Luo, Enhong Chen, and Tong Zhang. 2015. Matrix Factorization with Scale-Invariant Parameters. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 4017–4023. https://ijcai.org/proceedings/2015/564

@inproceedings{ijcai2015p564,
  title     = {Matrix Factorization with Scale-Invariant Parameters},
  author    = {Zeng, Guangxiang and Zhu, Hengshu and Liu, Qi and Luo, Ping and Chen, Enhong and Zhang, Tong},
  booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-15}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Qiang Yang and Michael Wooldridge},
  pages     = {4017--4023},
  year      = {2015},
  month     = {7},
  note      = {Special Track on Machine Learning},
  url       = {https://ijcai.org/proceedings/2015/564},
}

TY  - CPAPER
TI  - Matrix Factorization with Scale-Invariant Parameters
AU  - Zeng, Guangxiang
AU  - Zhu, Hengshu
AU  - Liu, Qi
AU  - Luo, Ping
AU  - Chen, Enhong
AU  - Zhang, Tong
T2  - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2015
SP  - 4017
EP  - 4023
UR  - https://ijcai.org/proceedings/2015/564
ER  -