Efficient Coreset Selection with Cluster-based Methods

Author:

Chai Chengliang1ORCID,Wang Jiayi2ORCID,Tang Nan3ORCID,Yuan Ye1ORCID,Liu Jiabin1ORCID,Deng Yuhao1ORCID,Wang Guoren1ORCID

Affiliation:

1. Beijing Institute of Technology, Beijing, China

2. Tsinghua University, Beijing, China

3. HKUST(GZ), Guangzhou, China

Funder

Huawei Technologies

NSF of China

Publisher

ACM

Reference47 articles.

1. https://www.kaggle.com/datasets/olistbr/brazilian-ecommerce/ 2023. Accessed: 2023-02-01. https://www.kaggle.com/datasets/olistbr/brazilian-ecommerce/ 2023. Accessed: 2023-02-01.

2. https://archive.ics.uci.edu/ml/datasets/covertype 2023. Accessed: 2023-02-01. https://archive.ics.uci.edu/ml/datasets/covertype 2023. Accessed: 2023-02-01.

3. Effcient coreset selection with cluster-based methods [technical report]. https: //github.com/for0nething/FCTR , 2023 . Last accessed: 2023-06-03. Effcient coreset selection with cluster-based methods [technical report]. https: //github.com/for0nething/FCTR, 2023. Last accessed: 2023-06-03.

4. M. Abadi , P. Barham , J. Chen , Z. Chen , A. Davis , J. Dean , M. Devin , S. Ghemawat , G. Irving , M. Isard , Tensorflow: a system for large-scale machine learning . In Osdi , volume 16 , pages 265 -- 283 . Savannah, GA , USA , 2016 . M. Abadi, P. Barham, J. Chen, Z. Chen, A. Davis, J. Dean, M. Devin, S. Ghemawat, G. Irving, M. Isard, et al. Tensorflow: a system for large-scale machine learning. In Osdi, volume 16, pages 265--283. Savannah, GA, USA, 2016.

5. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions

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