Learning Recommenders for Implicit Feedback with Importance Resampling-Reference-Cited by-同舟云学术

Learning Recommenders for Implicit Feedback with Importance Resampling

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2022
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Author:

Chen Jin¹,Lian Defu²,Jin Binbin³,Zheng Kai¹,Chen Enhong²

Affiliation:

1. University of Electronic Science and Technology of China, China

2. University of Science and Technology of China, China

3. Huawei Cloud Computing Technologies Co., Ltd., China

Funder

Shenzhen Municipal Science and Technology R&D Funding Basic Research Program

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3485447.3512075

Reference43 articles.

1. Yu Bai , Sally Goldman , and Li Zhang . 2017 . Tapas: Two-pass approximate adaptive sampling for softmax. arXiv preprint arXiv:1707.03073(2017). Yu Bai, Sally Goldman, and Li Zhang. 2017. Tapas: Two-pass approximate adaptive sampling for softmax. arXiv preprint arXiv:1707.03073(2017).

2. A Generic Coordinate Descent Framework for Learning from Implicit Feedback

3. Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model

4. Guy Blanc and Steffen Rendle . 2018 . Adaptive sampled softmax with kernel based sampling . In International Conference on Machine Learning. PMLR, 590–599 . Guy Blanc and Steffen Rendle. 2018. Adaptive sampled softmax with kernel based sampling. In International Conference on Machine Learning. PMLR, 590–599.

5. Improving One-Class Collaborative Filtering via Ranking-Based Implicit Regularizer

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