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Harshit Rawat

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#machine learning Preprint Aug 2026

Why Clipping Matters in AdaGrad? Toward a High-Probability Theory under Generalized Smoothness

This work analyzes the original same-step coordinate-wise AdaGrad under generalized smoothness and heavy-tailed noise with bounded variance and shows that clipping is a structural stabilizer of the adaptive geometry rather than merely a robustness heuristic for AdaGrad under heavy-tailed noise.

Alokendu Mazumder, Ayaan Mohd, Harshit Rawat et al. · 0 citations

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