Distributed Stochastic Gradient Method for Non-Convex Problems with Applications in Supervised Learn

時間 2020-12-20

標籤算法機器學習論文研讀简体版

原文原文鏈接

Distributed Stochastic Gradient Method for Non-Convex Problems with Applications in Supervised Learning Abstract We develop a distributed stochastic gradient descent algorithm for solving non-convex o

>>阅读原文<<

1. Distributed Stochastic Gradient Descent with Event-Triggered Communication
2. Stochastic Gradient Descent
3. ADAM A METHOD FOR STOCHASTIC OPTIMIZATION
4. Optimization Method -- Gradient Descent with Momentum Gradient Descent （轉）
5. Problems with EXC_BAD_ACCESS in CCBReader
6. (17)[NIPS16] ADAM: A METHOD FOR STOCHASTIC OPTIMIZATION
7. [Scikit-learn] 1.5 Generalized Linear Models - SGD for Regression
8. CS231Optimization: Stochastic Gradient Descent筆記
9. Truncated Power Method for Sparse Eigenvalue Problems
10. （轉）Applications of Reinforcement Learning in Real World
更多相關文章...
• Swift for-in 循環 - Swift 教程
• Lua for 循環 - Lua 教程
• 算法總結-股票買賣
• 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

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. Duang!超快Wi-Fi來襲
2. 機器學習-補充03 神經網絡之**函數(Activation Function)
3. git上開源maven項目部署多module maven項目（多module maven+redis+tomcat+mysql）後臺部署流程學習記錄
4. ecliple-tomcat部署maven項目方式之一
5. eclipse新導入的項目經常可以看到「XX cannot be resolved to a type」的報錯信息
6. Spark RDD的依賴於DAG的工作原理
7. VMware安裝CentOS-8教程詳解
8. YDOOK：Java 項目 Spring 項目導入基本四大 jar 包導入依賴，怎樣在 IDEA 的項目結構中導入 jar 包導入依賴
9. 簡單方法使得putty（windows10上）可以免密登錄樹莓派
10. idea怎麼用本地maven

本站公眾號

歡迎關注本站公眾號,獲取更多信息

1. Distributed Stochastic Gradient Descent with Event-Triggered Communication
2. Stochastic Gradient Descent
3. ADAM A METHOD FOR STOCHASTIC OPTIMIZATION
4. Optimization Method -- Gradient Descent with Momentum Gradient Descent （轉）
5. Problems with EXC_BAD_ACCESS in CCBReader
6. (17)[NIPS16] ADAM: A METHOD FOR STOCHASTIC OPTIMIZATION
7. [Scikit-learn] 1.5 Generalized Linear Models - SGD for Regression
8. CS231Optimization: Stochastic Gradient Descent筆記
9. Truncated Power Method for Sparse Eigenvalue Problems
10. （轉）Applications of Reinforcement Learning in Real World

>>更多相關文章<<