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stat.ML2026
The Price of Hidden Curvature: Improved Lower Bounds for Bandit Convex Optimization
Nived Rajaraman, Yanjun Han
We establish improved lower bounds on the minimax expected regret of stochastic bandit convex optimization for -Lipschitz functions on the -dimensional Euclidean ball. For ti…
stat.ML2026
Interactive Learning of Single-Index Models via Stochastic Gradient Descent
Nived Rajaraman, Yanjun Han
Stochastic gradient descent (SGD) is a cornerstone algorithm for high-dimensional optimization, renowned for its empirical successes. Recent theoretical advances have provided a de…