AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 2 of 2 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Random projections (RP) offer an effective method for reducing computational and storage overhead while preserving the geometric structure of data. However, existing studies have primarily focused on the optimal generalization performance of specific kernel-regularized algorithms with RP in the well-specified setting a...
This work proposes a neighboring early-stopping rule for adaptive regularization in KRR with random features (KRR-RF), using a grid that is uniform in inverse regularization and compares only adjacent estimators, reducing the number of discrepancy comparisons relative to standard all-pairs Lepskii-type procedures.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.