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stat.ML2026
Universal priors: solving empirical Bayes via Bayesian inference and pretraining
Nick Cannella, Anzo Teh, Yanjun Han +1
We theoretically justify the recent empirical finding of [Teh et al., 2025] that a transformer pretrained on synthetically generated data achieves strong performance on empirical B…
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…
stat.ML2025
Evolution of Information in Interactive Decision Making: A Case Study for Multi-Armed Bandits
Yuzhou Gu, Yanjun Han, Jian Qian
We study the evolution of information in interactive decision making through the lens of a stochastic multi-armed bandit problem. Focusing on a fundamental example where a unique o…