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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.

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hetankevin/probono

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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.

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