Code for the paper "Optimal Batched Linear Bandits", International Conference on Machine Learning (ICML) 2024
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Updated
May 30, 2024 - Python
Code for the paper "Optimal Batched Linear Bandits", International Conference on Machine Learning (ICML) 2024
Code for the paper "Truncated LinUCB for Stochastic Linear Bandits"
Algorithms for accelerating personalization (in the context of linear bandit recommendations) to new users, given access to embeddings from other users with heterogenous tastes and preferences. Novel algorithm for learning subspaces, which we exploit via a modified LinUCB algorithm. Accepted to ICML 2025.
algorithm implementations & practices
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