Stochastic Low-Rank Tensor Bandits for Multi-Dimensional Online Decision Making

Author:

Zhou Jie1,Hao Botao2,Wen Zheng2,Zhang Jingfei3ORCID,Sun Will Wei4

Affiliation:

1. Amazon, Seattle, WA

2. Deepmind, Mountain View, CA

3. Goizueta Business School, Emory University, Atlanta, GA

4. Daniels School of Business, Purdue University, West Lafayette, IN

Funder

NSF-SES

National Science Foundation

Publisher

Informa UK Limited

Reference51 articles.

1. “Improved Algorithms for Linear Stochastic Bandits,”;Abbasi-Yadkori Y.;Advances in Neural Information Processing Systems,2011

2. Accurate Online Tensor Factorization for Temporal Tensor Streams with Missing Values

3. Allen, G. (2012), “Sparse Higher-Order Principal Components Analysis,” in Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 22, 27–36.

4. Exploration–exploitation tradeoff using variance estimates in multi-armed bandits

5. “Using Confidence Bounds for Exploitation-Exploration Trade-offs,”;Auer P.;Journal of Machine Learning Research,2002

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