Ai Kagawa — accepted AI-conference papers

2026

Spatial Deconfounder: Interference-Aware Deconfounding for Spatial Causal Inference

Ayush Khot, Miruna Oprescu, Maresa Schröder, Ai Kagawa, Xihaier Luo

ICML 2026poster

Causal inference in spatial domains faces two intertwined challenges: (1) unmeasured spatial factors, such as weather, air pollution, or mobility, that confound treatment and outcome, and (2) interference from nearby treatments that violate standard no-interference assumptions. While existing method…

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2017

Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement

Jonathan Eckstein, Noam Goldberg, Ai Kagawa

ICML 2017poster

We describe a learning procedure enhancing L1-penalized regression by adding dynamically generated rules describing multidimensional “box” sets. Our rule-adding procedure is based on the classical column generation method for high-dimensional linear programming. The pricing problem for our column ge…

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