K. Mohammed

most citedManifold Learning Using Kernel Density Estimation and Local Principal Components Analysis

10 citations · 10 across the 2 of their papers we have counts for

collaborators

2 papers

stat.ML2018

Structural Risk Minimization for $C^{1, 1} (R^{d})$ Regression

Adam Gustafson, Matthew Hirn, Kitty Mohammed +2

One means of fitting functions to high-dimensional data is by providing smoothness constraints. Recently, the following smooth function approximation problem was proposed: given a…

math.ST2017★ 10 cited

Manifold Learning Using Kernel Density Estimation and Local Principal Components Analysis

Kitty Mohammed, Hariharan Narayanan

We consider the problem of recovering a $d -$ dimensional manifold $M \subset R^{n}$ when provided with noiseless samples from $M$ . There are many algorith…

Structural Risk Minimization for C1,1(Rd) Regression

Manifold Learning Using Kernel Density Estimation and Local Principal Components Analysis

Structural Risk Minimization for $C^{1, 1} (R^{d})$ Regression