We present experiments demonstrating that some other form of capacity
control, different from network size, plays a central role in learning
multilayer feed-forward networks. We argue, partially through analogy to matrix
factorization, that this is an inductive bias that can help shed light on deep
learning.
Description
[1412.6614] In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
%0 Journal Article
%1 neyshabur2014search
%A Neyshabur, Behnam
%A Tomioka, Ryota
%A Srebro, Nathan
%D 2014
%K deep-learning foundations machine-learning stable theory regularisation
%T In Search of the Real Inductive Bias: On the Role of Implicit
Regularization in Deep Learning
%U http://arxiv.org/abs/1412.6614
%X We present experiments demonstrating that some other form of capacity
control, different from network size, plays a central role in learning
multilayer feed-forward networks. We argue, partially through analogy to matrix
factorization, that this is an inductive bias that can help shed light on deep
learning.
@article{neyshabur2014search,
abstract = {We present experiments demonstrating that some other form of capacity
control, different from network size, plays a central role in learning
multilayer feed-forward networks. We argue, partially through analogy to matrix
factorization, that this is an inductive bias that can help shed light on deep
learning.},
added-at = {2019-06-10T11:26:58.000+0200},
author = {Neyshabur, Behnam and Tomioka, Ryota and Srebro, Nathan},
biburl = {https://www.bibsonomy.org/bibtex/2caa79cc374936649b23d212f1437aadd/kirk86},
description = {[1412.6614] In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning},
interhash = {e302965c2d22ac1a6924d47fa8b61114},
intrahash = {caa79cc374936649b23d212f1437aadd},
keywords = {deep-learning foundations machine-learning stable theory regularisation},
note = {cite arxiv:1412.6614Comment: 9 pages, 2 figures},
timestamp = {2019-09-26T16:00:39.000+0200},
title = {In Search of the Real Inductive Bias: On the Role of Implicit
Regularization in Deep Learning},
url = {http://arxiv.org/abs/1412.6614},
year = 2014
}