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Code repository for the work Relational Boosted Bandits, AAAI'21

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Relational-Boosted-Bandits

Code repository for the work Relational Boosted Bandits, AAAI'21

Contextual bandits algorithms have become essential in real-world user interaction problems in recent years. However, these algorithms rely on context as attribute value representation, which makes them unfeasible for real-world domains like social networks are inherently relational. We propose Relational Boosted Bandits(RB2), acontextual bandits algorithm for relational domains based on (relational) boosted trees. RB2 enables us to learn interpretable and explainable models due to the more descriptive nature of the relational representation. We empirically demonstrate the effectiveness and interpretability of RB2 on tasks such as link prediction, relational classification, and recommendations

Paper Link: https://arxiv.org/pdf/2012.09220.pdf

Authors: Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran

Reach-out for queries and discussion: Ashutosh Kakadiya, ashutoshkakadiya11@gmail.com

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Code repository for the work Relational Boosted Bandits, AAAI'21

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  • Python 100.0%