JavaShuo
欄目
標籤
【ML&DL】【skimming】The Loss Surfaces of Multilayer Networks
時間 2021-01-02
標籤
ML&DL
機器學習
深度學習
人工智能
欄目
Microsoft Surface
简体版
原文
原文鏈接
補了一下Yann LeCun的經典工作The Loss Surfaces of Multilayer Networks[1] 論文一覽: 痛點 文章假設並且陸續證明了這樣一些事情: 1)對於大網絡(large size network)而言,絕大多數局部極小值在test上的表現是差不多的,且這些local minima跟global minima的表現也是差不多的。 2)小網絡找到差的局部極小值(
>>阅读原文<<
相關文章
1.
【ML&DL】【skimming】On the saddle point problem for non-convex optimization
2.
Multilayer Neural Networks and the Backpropagation Learning Algorithm
3.
The Multilinear Structure of ReLU Networks
4.
Multilayer in-place learning networks for modeling functional layers in the laminar cortex筆記
5.
The Unreasonable Effectiveness of Recurrent Neural Networks
6.
Exploring the teaching of deep learning in neural networks
7.
On the Number of Linear Regions of Deep Neural Networks
8.
In Defense of the Triplet Loss for Person Re-Identification
9.
Deep Learning 101 - Part 2: Multilayer Perceptrons
10.
The Lovasz-Softmax loss: A tractable surrogate for the optimization of the ´ intersection-over-union
更多相關文章...
•
XSLT
元素
-
XSLT 教程
•
XSLT
元素
-
XSLT 教程
•
JDK13 GA發佈:5大特性解讀
•
爲了進字節跳動,我精選了29道Java經典算法題,帶詳細講解
相關標籤/搜索
networks
surfaces
loss
for...of
for..of
mysql..the
the&nbs
mysql....the
The One!
5.the
Microsoft Surface
Spring教程
0
分享到微博
分享到微信
分享到QQ
每日一句
每一个你不满意的现在,都有一个你没有努力的曾经。
最新文章
1.
安裝cuda+cuDNN
2.
GitHub的使用說明
3.
phpDocumentor使用教程【安裝PHPDocumentor】
4.
yarn run build報錯Component is not found in path 「npm/taro-ui/dist/weapp/components/rate/index「
5.
精講Haproxy搭建Web集羣
6.
安全測試基礎之MySQL
7.
C/C++編程筆記:C語言中的複雜聲明分析,用實例帶你完全讀懂
8.
Python3教程(1)----搭建Python環境
9.
李宏毅機器學習課程筆記2:Classification、Logistic Regression、Brief Introduction of Deep Learning
10.
阿里雲ECS配置速記
本站公眾號
歡迎關注本站公眾號,獲取更多信息
相關文章
1.
【ML&DL】【skimming】On the saddle point problem for non-convex optimization
2.
Multilayer Neural Networks and the Backpropagation Learning Algorithm
3.
The Multilinear Structure of ReLU Networks
4.
Multilayer in-place learning networks for modeling functional layers in the laminar cortex筆記
5.
The Unreasonable Effectiveness of Recurrent Neural Networks
6.
Exploring the teaching of deep learning in neural networks
7.
On the Number of Linear Regions of Deep Neural Networks
8.
In Defense of the Triplet Loss for Person Re-Identification
9.
Deep Learning 101 - Part 2: Multilayer Perceptrons
10.
The Lovasz-Softmax loss: A tractable surrogate for the optimization of the ´ intersection-over-union
>>更多相關文章<<