Biconvex Biclustering
This article proposes a biconvex modification to convex biclustering in order to improve its performance in high-dimensional settings. In contrast to heuristics that discard a subset of noisy features a priori, our method jointly learns and accordingly weighs informative features while discovering biclusters. Moreover, the method is adaptive to the data, and is accompanied by an efficient algorithm based on proximal alternating minimization, complete with detailed guidance on hyperparameter tuning and efficient solutions to optimization subproblems. These contributions are theoretically grounded; we establish finite-sample bounds on the objective function under sub-Gaussian errors, and ge...
| Authors | Sam Rosen, Eric C. Chi, Jason Xu |
|---|---|
| Primary category | stat.ML |
| Published | 5 April 2026 |
| Last updated at source | 5 April 2026 |
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