Concentration of measure for non-linear random matrices with applications to neural networks and non-commutative polynomials
–arXiv.org Artificial Intelligence
We prove concentration inequalities for several models of non-linear random matrices. As corollaries we obtain estimates for linear spectral statistics of the conjugate kernel of neural networks and non-commutative polynomials in (possibly dependent) random matrices.
arXiv.org Artificial Intelligence
Jul-15-2025
- Country:
- Africa > Middle East
- Tunisia > Ben Arous Governorate > Ben Arous (0.04)
- Europe
- France (0.04)
- Italy > Sardinia (0.04)
- Poland > Masovia Province
- Warsaw (0.04)
- United Kingdom
- England > Cambridgeshire
- Cambridge (0.04)
- North Sea > Southern North Sea (0.04)
- England > Cambridgeshire
- North America
- Canada > Ontario
- Toronto (0.04)
- Mexico > Oaxaca (0.04)
- United States
- Massachusetts > Middlesex County
- Cambridge (0.04)
- New York (0.04)
- Rhode Island > Providence County
- Providence (0.04)
- Massachusetts > Middlesex County
- Canada > Ontario
- Africa > Middle East
- Genre:
- Research Report (0.82)
- Technology: