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stat.ME2026
Bias-Corrected Subspace Intersection: Minimax-Optimal Shared Subspace Estimation in Multi-View Data
Xianwen Song, Yuepeng Yang, Cong Ma
Estimating a low-dimensional subspace shared across noisy data matrices is a fundamental problem in multi-view matrix estimation. We study this problem under the two-view JIVE mode…
cs.LG2026
Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions
Yuepeng Yang, Yuxin Chen, Yuejie Chi
Distributionally robust Markov decision processes provide a principled framework for sequential decision making under model uncertainty. We study how many samples are necessary and…
stat.ML2026
Sample-efficient inductive matrix completion with noise and inexact side-information
Yuepeng Yang, Cong Ma
Inductive matrix completion (IMC) is a variant of low-rank matrix completion that incorporates row and column side-information. In principle, it can reduce the effective dimension…