226 citations · 750 across the 46 of their papers we have counts for
8 papers · 1 filter
Formal Analysis of Art: Proxy Learning of Visual Concepts from Style Through Language Models
Diana Kim, Ahmed Elgammal, Marian Mazzone
We present a machine learning system that can quantify fine art paintings with a set of visual elements and principles of art. This formal analysis is fundamental for understanding…
Spatial Frequency Bias in Convolutional Generative Adversarial Networks
Mahyar Khayatkhoei, Ahmed Elgammal
As the success of Generative Adversarial Networks (GANs) on natural images quickly propels them into various real-life applications across different domains, it becomes more and mo…
Disconnected Manifold Learning for Generative Adversarial Networks
Mahyar Khayatkhoei, Ahmed Elgammal, Maneesh Singh
Natural images may lie on a union of disjoint manifolds rather than one globally connected manifold, and this can cause several difficulties for the training of common Generative A…
Overlapping Cover Local Regression Machines
Mohamed Elhoseiny, Ahmed Elgammal
We present the Overlapping Domain Cover (ODC) notion for kernel machines, as a set of overlapping subsets of the data that covers the entire training set and optimized to be spatia…
Learning Kernels for Structured Prediction using Polynomial Kernel Transformations
Chetan Tonde, Ahmed Elgammal
Learning the kernel functions used in kernel methods has been a vastly explored area in machine learning. It is now widely accepted that to obtain 'good' performance, learning a ke…
Supervised Dimensionality Reduction via Distance Correlation Maximization
Praneeth Vepakomma, Chetan Tonde, Ahmed Elgammal
In our work, we propose a novel formulation for supervised dimensionality reduction based on a nonlinear dependency criterion called Statistical Distance Correlation, Szekely et. a…
Generalized Twin Gaussian Processes using Sharma-Mittal Divergence
Mohamed Elhoseiny, Ahmed Elgammal
There has been a growing interest in mutual information measures due to their wide range of applications in Machine Learning and Computer Vision. In this paper, we present a genera…
DISCOMAX: A Proximity-Preserving Distance Correlation Maximization Algorithm
Praneeth Vepakomma, Ahmed Elgammal
In a regression setting we propose algorithms that reduce the dimensionality of the features while simultaneously maximizing a statistical measure of dependence known as distance c…