Skip to main content

Blog

Learn About Our Meetup

5000+ Members

MEETUPS

LEARN, CONNECT, SHARE

Join our meetup, learn, connect, share, and get to know your Toronto AI community. 

JOB POSTINGS

INDEED POSTINGS

Browse through the latest deep learning, ai, machine learning postings from Indeed for the GTA.

CONTACT

CONNECT WITH US

Are you looking to sponsor space, be a speaker, or volunteer, feel free to give us a shout.

[R]: Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates

The authors use a classic Armijo line-search approach in the context of SGD to automatically tune the line search parameter in training the neural networks. They’re also able to prove convergence results on minimizing convex and non-convex objective functions satisfying certain growth conditions. An aside, but as an optimization-head myself, it’s nice to see some of the traditional optimization ideas make their way into an ML context.

https://arxiv.org/pdf/1905.09997.pdf

submitted by /u/sinsecticide
[link] [comments]