A Learning-Rate Schedule for Stochastic Gradient Methods to Matrix Factorization

@inproceedings{Chin2015ALS,
  title={A Learning-Rate Schedule for Stochastic Gradient Methods to Matrix Factorization},
  author={Wei-Sheng Chin and Yong Zhuang and Yu-Chin Juan and Chih-Jen Lin},
  booktitle={PAKDD},
  year={2015}
}
Stochastic gradient methods are effective to solve matrix factorization problems. However, it is well known that the performance of stochastic gradient method highly depends on the learning rate schedule used; a good schedule can significantly boost the training process. In this paper, motivated from past works on convex optimization which assign a learning rate for each variable, we propose a new schedule for matrix factorization. The experiments demonstrate that the proposed schedule leads to… CONTINUE READING
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