Author

Anish Agarwal

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Preprint Sep 2026

Synthetic Nearest Neighbors: Extending Synthetic Controls for Matrix Completion with Missing Not at Random Data

We develop a causal framework for matrix completion under missing not at random (MNAR) data. Drawing on synthetic controls from the econometric panel data literature, our approach relaxes two assumptions common in MNAR matrix completion: positivity and independence of observation indicators. Unlike traditional panel da...

Anish Agarwal, M. Dahleh, Devavrat Shah et al. · 0 citations

#machine learning Preprint Oct 2022

Synthetic Blips: Generalizing Synthetic Controls for Dynamic Treatment Effects

We propose a generalization of the synthetic control methods to the setting with dynamic treatment effects, in which each unit receives multiple treatments sequentially, according to an adaptive policy that depends on a latent, endogenously time-varying confounding state. Under a low-rank latent factor model assumption...

Anish Agarwal, Sukjin Han, Dwaipayan Saha et al. · 3 citations