A Generalized Locally Linear Factorization Machine with Supervised Variational Encoding

2020 ◽  
Vol 32 (6) ◽  
pp. 1036-1049
Author(s):  
Xiaoshuang Chen ◽  
Yin Zheng ◽  
Peilin Zhao ◽  
Zhuxi Jiang ◽  
Wenye Ma ◽  
...  
Keyword(s):  
Factorization Machine ◽  
Linear Factorization ◽  
Locally Linear

scholarly journals Locally Linear Factorization Machines

2017 ◽  
Author(s):  
Chenghao Liu ◽  
Teng Zhang ◽  
Peilin Zhao ◽  
Jun Zhou ◽  
Jianling Sun
Keyword(s):  
Predictive Accuracy ◽  
High Order ◽  
Anchor Point ◽  
Complex Data ◽  
Coding Scheme ◽  
Feature Interactions ◽  
Label Information ◽  
Local Coding ◽  
Linear Factorization ◽  
Locally Linear

Factorization Machines (FMs) are a widely used method for efficiently using high-order feature interactions in classification and regression tasks. Unfortunately, despite increasing interests in FMs, existing work only considers high order information of the input features which limits their capacities in non-linear problems and fails to capture the underlying structures of more complex data. In this work, we present a novel Locally Linear Factorization Machines (LLFM) which overcomes this limitation by exploring local coding technique. Unlike existing local coding classifiers that involve a phase of unsupervised anchor point learning and predefined local coding scheme which is suboptimal as the class label information is not exploited in discovering the encoding and thus can result in a suboptimal encoding for prediction, we formulate a joint optimization over the anchor points, local coding coordinates and FMs variables to minimize classification or regression risk. Empirically, we demonstrate that our approach achieves much better predictive accuracy than other competitive methods which employ LLFM with unsupervised anchor point learning and predefined local coding scheme.

Locally Linear Embedding Based on Relative Manifold

2009 ◽  
Vol 20 (9) ◽  
pp. 2376-2386 ◽  
Author(s):  
Gui-Hua WEN ◽  
Ting-Hui LU ◽  
Li-Jun JIANG ◽  
Jun WEN
Keyword(s):  
Locally Linear Embedding ◽  
Linear Embedding ◽  
Locally Linear

Nonuniform Spatial Deformation of Light Fields by Locally Linear Transformations

2017 ◽  
Vol 36 (4) ◽  
pp. 1
Author(s):  
Clemens Birklbauer ◽  
David C. Schedl ◽  
Oliver Bimber
Keyword(s):  
Light Fields ◽  
Linear Transformations ◽  
Spatial Deformation ◽  
Locally Linear

Bearing feature extraction using multi-structure locally linear embedding

2021 ◽  
Vol 428 ◽  
pp. 280-290
Author(s):  
Yuanhong Liu ◽  
Zebiao Hu ◽  
Yansheng Zhang
Keyword(s):  
Feature Extraction ◽  
Locally Linear Embedding ◽  
Linear Embedding ◽  
Locally Linear
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