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math.SP2024
The graph -Laplacian eigenvalue problem
Piero Deidda, Martin Burger, Mario Putti +1
We analyze various formulations of the -Laplacian eigenvalue problem on graphs, comparing their properties and highlighting their respective advantages and limitations. Fir…
math.NA2024
Graph -Laplacian eigenpairs as saddle points of a family of spectral energy functions
Piero Deidda, Nicola Segala, Mario Putti
We address the problem of computing the graph -Laplacian eigenpairs for . We propose a reformulation of the graph -Laplacian eigenvalue problem in terms of a…
cs.LG2024
Provable Emergence of Deep Neural Collapse and Low-Rank Bias in -Regularized Nonlinear Networks
Emanuele Zangrando, Piero Deidda, Simone Brugiapaglia +2
We present a unified theoretical framework connecting the first property of Deep Neural Collapse (DNC1) to the emergence of implicit low-rank bias in nonlinear networks trained wit…