5 citations · 8 across the 8 of their papers we have counts for
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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…
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)…
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…
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…