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cs.LG2026
CoreFlow: Low-Rank Matrix Generative Models
Dongze Wu, Linglingzhi Zhu, Yao Xie
Learning matrix-valued distributions from high-dimensional and possibly incomplete training data is challenging: ambient-space generative modeling is computationally expensive and…
cs.LG2026
Generative models for decision-making under distributional shift
Xiuyuan Cheng, Yunqin Zhu, Yao Xie
Many data-driven decision problems are formulated using a nominal distribution estimated from historical data, while performance is ultimately determined by a deployment distributi…