A simpler approach to obtaining an O(1/t) convergence rate for projected stochastic subgradient descent
By: Researcher II
Disclaimer: The provided code links for this paper are external links. Science Nest has no responsibility for the accuracy, legality or content of these links. Also, by downloading this code(s), you agree to comply with the terms of use as set out by the author(s) of the code(s).
| Authors | Simon Lacoste-Julien, Mark W. Schmidt, Francis R. Bach |
| Journal/Conference Name | ARXIV: LEARNING |
| Paper Category | Computer Science |
| Paper Abstract | In this note, we present a new averaging technique for the projected stochastic subgradient method. By using a weighted average with a weight of t+1 for each iterate w_t at iteration t, we obtain the convergence rate of O(1/t) with both an easy proof and an easy implementation. The new scheme is compared empirically to existing techniques, with similar performance behavior. |
| Date of publication | 2012 |
| Code Programming Language | MATLAB/C |
| Comment |
Copyright Researcher II 2022