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Found 3 papers, 2 papers with code
Effective Off-Policy Evaluation and Learning in Contextual Combinatorial Bandits
We explore off-policy evaluation and learning (OPE/L) in contextual combinatorial bandits (CCB), where a policy selects a subset in the action space.
Diffusion Model in Causal Inference with Unmeasured Confounders
We study how to extend the use of the diffusion model to answer the causal question from the observational data under the existence of unmeasured confounders.
Doubly Robust Estimator for Off-Policy Evaluation with Large Action Spaces
To overcome these limitations, Marginalized Inverse Propensity Scoring (MIPS) was proposed to mitigate the estimator's variance via embeddings of an action.
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