2 papers
cs.LG2026
Spectral Flattening Is All Muon Needs: How Orthogonalization Controls Learning Rate and Convergence
Tien-Phat Nguyen, Truong Nguyen, Minh-Phuc Truong +3
Muon orthogonalizes the momentum buffer before each update, replacing its singular values with ones via Newton-Schulz iterations. This simple change lets Muon tolerate far larger l…
cs.LG2026
On the Use of Bagging for Local Intrinsic Dimensionality Estimation
Kristóf Péter, Ricardo J. G. B. Campello, James Bailey +1
The theory of Local Intrinsic Dimensionality (LID) has become a valuable tool for characterizing local complexity within and across data manifolds, supporting a range of data minin…