PAC-Bayesian lifelong learning for multi-armed bandits

Author:

Flynn HamishORCID,Reeb David,Kandemir Melih,Peters Jan

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Information Systems

Reference46 articles.

1. Amit R, Mier R (2018) Meta-learning by adjusting priors based on extended PAC-Bayes theory. Int Conf Mach Learn 205–214

2. Azar MG, Lazaric A, Brunskill E (2013) Sequential transfer in multi-armed bandit with finite set of models. Adv Neural Inf Process Syst

3. Azuma K (1967) Weighted sums of certain dependent random variables. Tohoku Math J Second Ser 19:357–367

4. Balsubramani A (2015) PAC-Bayes iterated logarithm bounds for martingale mixtures. arXiv preprint. arXiv:1506.06573

5. Banerjee A (2006) On Bayesian bounds. In: Proceedings of the 23rd international conference on machine learning, pp 81–88

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1. PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023-12

2. Prototype-Guided Feature Learning for Unsupervised Domain Adaptation;Pattern Recognition;2023-03

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