-
Upload Video
videos in mp4/mov/flv
close
Upload video
Note: publisher must agree to add uploaded document -
Feedback
help us improve
close
Feedback
Please help us improve your experience by sending us a comment, question or concern
Please help transcribe this video using our simple transcription tool. You need to be logged in to do so.
Description
The goal of the presentation is to describe practical stochastic gradient algorithms that process each training
example only once, yet asymptotically match the performance of the true optimum. This statement needs, of
course, to be made more precise. To achieve this, we'll review the works of Nevel'son and Has'minskij (1972),
Fabian (1973, 1978), Murata & Amari (1998), Bottou & LeCun (2004), Polyak & Juditsky (1992), Wei Xu (2010),
and Bach & Moulines (2011). We will then show how these ideas lead to practical algorithms that not only
represent a new state of the art but are also arguably optimal.
Questions and Answers
You need to be logged in to be able to post here.-
-
-
Q:Posted by: | July 11, 2018, 12:25 p.m. | 0 likes
I can't watch the video. It seems there is no resource. It would be great if anyone can fix this! Thanks!
-