71 citations · 214 across the 20 of their papers we have counts for
4 papers · 1 filter
Generative Adversarial Parallelization
Daniel Jiwoong Im, He Ma, Chris Dongjoo Kim +1
Generative Adversarial Networks have become one of the most studied frameworks for unsupervised learning due to their intuitive formulation. They have also been shown to be capable…
An empirical analysis of the optimization of deep network loss surfaces
Daniel Jiwoong Im, Michael Tao, Kristin Branson
The success of deep neural networks hinges on our ability to accurately and efficiently optimize high-dimensional, non-convex functions. In this paper, we empirically investigate t…
Learning a metric for class-conditional KNN
Daniel Jiwoong Im, Graham W. Taylor
Naive Bayes Nearest Neighbour (NBNN) is a simple and effective framework which addresses many of the pitfalls of K-Nearest Neighbour (KNN) classification. It has yielded competitiv…
Generating images with recurrent adversarial networks
Daniel Jiwoong Im, Chris Dongjoo Kim, Hui Jiang +1
Gatys et al. (2015) showed that optimizing pixels to match features in a convolutional network with respect reference image features is a way to render images of high visual qualit…