Abstract:Researchers often face data fusion problems, where multiple data sources are available, each capturing a distinct subset of variables. While problem formulations typically take the data as given, in practice, data acquisition can be an ongoing process. In this paper, we aim to estimate any functional of a probabilistic model (e.g., a causal e ect) as e ciently as possible, by deciding, at each time, which data source to query. We propose online moment selection (OMS), a framework in which structural assumption… Show more
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