Vicarious AI's Generative Models for Training with Very Little Data

SF Big Analytics
SF Big Analytics
Public group
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I am very please to have invited Dr. Xinghua Lou from Vicarious to talk about the recent paper originally presented at NIPS 2016.

Title:

Vicarious AI's Generative Models for Training with Very Little Data

Summary:
Vicarious AI is an artificial intelligence core technology R&D startup based in Silicon Valley, USA. Vicarious approaches AI with a very unique brain-inspired strategy, drawing inspirations from neuroscience and cognitive science and combining them with modern computational modeling techniques such as probabilistic graphical models (PGM). In this talk, we will present Vicarious' recent papers on generative shape models and hierarchical feature learning. We will discuss our performance on public text recognition benchmarks and show how to outperform deep learning using 6000 times less amount of training data.

Bio:
Xinghua Lou, Ph.D., is Head of Commercialization at Vicarious AI. Xinghua is a veteran machine learning researcher and practitioner. He has published in many renowned venues such as NIPS, ICML, CVPR, MIT Press, and has won the best paper award in 2012 Machine Learning for Medical Imaging. Xinghua's current interest is connecting Vicarious AI to impactful real world applications.

LinkedIn: https://www.linkedin.com/in/xinghualou

Agenda:

6 pm -- Door opens

7 pm -- check-in closed, Yelp entrance closed

6 pm -- 6:30pm check-in, networking + pizza/drinks

6:30 pm -- 7:30 pm Main talk

7:30 pm -- 7:45 pm Q & A

7:45 pm -- 8: 15 pm closing

8:30 pm Event closed