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Apple Publishes Artificial Intelligence Paper for the First Time Ever Lead by UMD Alumnus

Apple Publishes Artificial Intelligence Paper for the First Time Ever Lead by UMD Alumnus


Last month, Apple made an exciting announcement that they would begin publishing AI papers of their own, marking a momentous change in strategy that could accelerate advances in deep learning by allowing its AI engineers to engage openly with others, as noted in a Bloomberg article.

Alumnus Ashish Shrivastava, who was advised during his Ph.D. studies by ECE Department Chair and Minta Martin Professor Rama Chellappa (ECE/UMIACS), is the lead author on the very first published AI paper by Apple on December 22, 2016. The paper describes a technique for how to improve the training of an algorithm’s ability to recognize images using computer-generated images rather than real-world images.

In machine learning research, using synthetic images to train neural networks can be more efficient then using real world images due to the fact that synthetic image data is pre-labeled and annotated. However, learning from synthetic images may not achieve preferred performance due to a gap between synthetic and real image distributions. To decrease this gap and improve training with synthetic image data, Shrivastava and his colleagues suggest Simulated+Unsupervised (S+U) learning, where the realism of a simulated image is boosted. The Apple researchers use a modified version of a new machine learning technique called Generative Adversarial Networks, which pits two neural networks against each other and has been used to generate photorealistic images.

Shrivastava’s research interests are in Deep Learning, Computer Vision, Machine Learning, Convex Optimization and Signal Processing.

The other Apple researchers listed as co-authors on the paper include Tomas Pfister, Oncel Tuzel, Josh Susskind, Wenda Wang, and Russ Webb.

Related Articles:
Alumnus Aswin Sankaranarayanan Wins Excellence in Teaching Award at Carnegie Mellon University
PhD student Upal Mahbub and Prof. Rama Chellappa win IEEE UEMCON best paper award 
Chellappa to Receive Distinguished Alumnus Award from Indian Institute of Science
Chellappa Named Distinguished University Professor
RC65 Honors Chellappa’s 65th Birthday and his Academic Contributions to Computer Vision Research
Dinesh Manocha Joins ECE as the Paul Chrisman Iribe Professor of Computer Science
Wired Magazine Features Ott and Collaborators’ work on Machine Learning to Predict Chaos 
Dinesh Manocha Elected AAAI Fellow
Alumnus Profile: Jameel Francis
Papamanthou Gives Keynote at FAB 2018

January 5, 2017


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