Debiased Collaborative Filtering with Kernel-Based Causal Balancing

arXiv:2404.19596v1 Announce Type: cross
Abstract: Debiased collaborative filtering aims to learn an unbiased prediction model by removing different biases in observational datasets. To solve this problem, one of the simple and effective methods is based on the propensity score, which adjusts the observational sample distribution to the target one by reweighting observed instances. Ideally, propensity scores should be learned with causal balancing constraints. However, existing methods usually ignore such constraints or implement them with unreasonable approximations, which may affect the …

arxiv causal collaborative collaborative filtering cs.ir cs.lg filtering kernel type