activity
20242026
collaborators

5 papers

stat.ME2026

Flexible Inference for Winners with Conditional Validity

Soham Bakshi, Lingjun Gao, Zijun Gao +1

Researchers often select top-performing options or winners, based on a data-driven criterion, such as treatments, models, or model features and then report effect estimates for the…

stat.ME2026

Classification Trees with Valid Inference via the Exponential Mechanism

Soham Bakshi, Snigdha Panigrahi

Decision trees are widely used for non-linear modeling, as they capture interactions between predictors while producing inherently interpretable models. Despite their popularity, p…

stat.ML2026

From Collapse to Improvement: Statistical Perspectives on the Evolutionary Dynamics of Iterative Training on Contaminated Sources

Soham Bakshi, Sunrit Chakraborty

The problem of model collapse has presented new challenges in iterative training of generative models, where such training with synthetic data leads to an overall degradation of pe…

stat.ME2025

Inference with Randomized Regression Trees

Soham Bakshi, Yiling Huang, Snigdha Panigrahi +1

Regression trees are a popular machine learning algorithm that fit piecewise constant models by recursively partitioning the predictor space. This paper focuses on statistical infe…

stat.ME2024

Selective Inference for Time-Varying Moderated Effects

Soham Bakshi, Walter Dempsey, Snigdha Panigrahi

Causal effect moderation investigates how the effect of interventions (or treatments) on outcome variables changes based on observed characteristics of individuals, known as potent…