4 papers
cs.LG2026
Loss-Parameterized Fisher Width Along Learning Trajectories
Vu Khac Ky
Fisher width measures the Gaussian width of a probe set after deformation by the local Fisher geometry. We study its evolution along learning trajectories and ask when training los…
math.OC2026
Curvature Residual Geometry in Bregman Regression
Vu Khac Ky
We consider linear regression models fitted by minimizing Bregman losses of the form \[ \frac{1}{n}\sum_{i=1}^n \left[ ϕ(y_i)-ϕ(x_i^\topθ) -ϕ'(x_i^\topθ) \bigl(y_i-x_i^\topθ\bigr)…
cs.LG2026
Fisher Widths: Local Learning Geometry and Anisotropic Recovery
Vu Khac Ky
We study Gaussian-width complexity on statistical manifolds through a pair of functionals: the primal Fisher width , induced by the Fisher metric, and the inv…
cs.LG2026
Fisher Width: A Geometric Measure of Complexity on Statistical Manifolds
Vu Khac Ky
Gaussian width is a central geometric complexity measure in high-dimensional probability, compressed sensing, convex optimization, and learning theory. It quantifies the average ex…