Abhik Ghosh

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20232026

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math.ST2026

Universally Optimal Robustness-Efficiency Tradeoffs for a General Class of Minimum Divergence Estimators

Subhrajyoty Roy, Supratik Basu, Abhik Ghosh +1

Balancing the efficiency of an estimator under ideal conditions against its robustness under contamination remains a central challenge in robust statistics. While minimum divergenc…

stat.ML2026

Provably robust learning of regression neural networks using $β$ -divergences

Abhik Ghosh, Suryasis Jana

Regression neural networks (NNs) are most commonly trained by minimizing the mean squared prediction error, which is highly sensitive to outliers and data contamination. Existing r…

Universally Optimal Robustness-Efficiency Tradeoffs for a General Class of Minimum Divergence Estimators

Provably robust learning of regression neural networks using β-divergences

Provably robust learning of regression neural networks using $β$ -divergences