research
∙
08/19/2022
IAN: Iterated Adaptive Neighborhoods for manifold learning and dimensionality estimation
Invoking the manifold assumption in machine learning requires knowledge ...
share
research
∙
08/19/2020
On Qualitative Shape Inferences: a journey from geometry to topology
Shape inference is classically ill-posed, because it involves a map from...
research
∙
05/16/2020
From Boundaries to Bumps: when closed (extremal) contours are critical
Invariants underlying shape inference are elusive: a variety of shapes c...
research
∙
11/25/2017
Feature Selection Facilitates Learning Mixtures of Discrete Product Distributions
Feature selection can facilitate the learning of mixtures of discrete ra...
research
∙
05/20/2017
Critical Contours: An Invariant Linking Image Flow with Salient Surface Organization
We exploit a key result from visual psychophysics -- that individuals pe...
research
∙
05/16/2017
What's In A Patch, II: Visualizing generic surfaces
We continue the development of a linear algebraic framework for the shap...
research
∙
05/16/2017
What's In A Patch, I: Tensors, Differential Geometry and Statistical Shading Analysis
We develop a linear algebraic framework for the shape-from-shading probl...
research
∙
06/09/2015
Stagewise Learning for Sparse Clustering of Discretely-Valued Data
The performance of EM in learning mixtures of product distributions ofte...
research
∙
06/23/2013
