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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68252
Title: | 大規模分解機器之最佳化方法比較 A Comparison of Optimization Methods for Large Scale Factorization Machine |
Authors: | Chih-Yao Chang 張智堯 |
Advisor: | 林智仁(Chih-Jen Lin) |
Keyword: | 交替架構,牛頓法,常見方向方法,分解機器, alternating framework,Newton method,common-directions method,Factorization Machine, |
Publication Year : | 2017 |
Degree: | 碩士 |
Abstract: | 近年來,非凸最佳化問題變得相當熱門。非凸最佳化問題是個充滿許多未知數的領域,也非常值得花費力氣去研究最佳化方法在這類問題上的行為模式。此外,分解機器也漸漸廣泛地被使用在各類型的應用上面,特別是推薦系統。為了深入了解,我們分析了交替牛頓法以及常見方向在分解機器上的行為。本作品的主要貢獻是:詳細的比較了模型之間的相對目標函式值、訓練時間、偽數據遍歷。實驗結果顯示交替常見方向在收斂速度上較交替牛頓法來的快。 Recently, non-convex optimization has been a popular domain. Non-convex optimization is a domain full of unknowns and it is worth investigating behaviors of optimzation techniques on such kind of problems. Also, Factorization Machine has also been a popular model in many applications, especially for recommendation systems. To know the details, we analyze the behaviors of alternating Newton method (ANT) and alternating common-directions method on the model. In this work, we compare their relative objective function value, training time, and pseudo data passe. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68252 |
DOI: | 10.6342/NTU201704285 |
Fulltext Rights: | 有償授權 |
Appears in Collections: | 資訊工程學系 |
Files in This Item:
File | Size | Format | |
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ntu-106-1.pdf Restricted Access | 3.71 MB | Adobe PDF |
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