Diptesh Das — accepted AI-conference papers

2026

Statistically Robust Sparse High-order Interaction Model

Diptesh Das, Ichiro Takeuchi, Koji Tsuda

AAAI 2026technical

Deep learning models often achieve high accuracy but lack interpretability, making them unsuitable for critical applications such as medical diagnosis, biomolecule design, criminal justice, etc. The Sparse High-order Interaction Model (SHIM) addresses this limitation by providing both transparency a

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2022

Fast and More Powerful Selective Inference for Sparse High-Order Interaction Model

Diptesh Das, Vo Nguyen Le Duy, Hiroyuki Hanada, Koji Tsuda, Ichiro Takeuchi

AAAI 2022technical

Automated high-stake decision-making, such as medical diagnosis, requires models with high interpretability and reliability. We consider the sparse high-order interaction model as an interpretable and reliable model with a good prediction ability. However, finding statistically significant high-orde…

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