Feature Extraction for Incomplete Data Via Low-Rank Tensor Decomposition With Feature Regularization

Keyphrases

• Incomplete Data 100%
• Feature Extraction 100%
• Feature Regularization 100%
• Feature Variance 100%
• Low-rank Tensor Decomposition 100%
• Variance Maximization 83%
• Tensor Decomposition 66%
• Missing Entries 50%
• Alternating Direction multiplier Method 16%
• Face Recognition 16%
• Machine Learning 16%
• Real Image 16%
• Computer Vision 16%
• Pattern Recognition 16%
• Video Data 16%
• Gait 16%
• Low-rank 16%
• Image Data 16%
• Challenging Problems 16%
• Superior Performance 16%
• Weight Vector 16%
• Core Tensor 16%
• Multidimensional Data 16%
• Tucker Decomposition 16%
• Unified Framework 16%
• Effective Feature 16%
• Real-time Video 16%
• Informative Features 16%
• Extracting Features 16%
• Unsupervised Learning Environment 16%
• Low-rank Tensor Approximation 16%
• CP Model 16%
• Tucker Model 16%
• Tensor Completion 16%
• CP Decomposition 16%
• Orthogonal Tucker Decompositions 16%
• Low-dimensional Features 16%
• Block Coordinate Descent 16%
• Optimization Scheme 16%
• Maximization Methods 16%
• Feature Extracting 16%
• Learning Patterns 16%
• Joint Optimization 16%
• Missing Data Estimation 16%
• Completion Method 16%
• Action Classification 16%

Computer Science

• Regularization 100%
• Feature Extraction 100%
• Approximation (Algorithm) 66%
• Extracted Feature 66%
• Experimental Result 33%
• Face Recognition 33%
• Machine Learning 33%
• Learning System 33%
• Pattern Recognition 33%
• Unsupervised Learning 33%
• Multidimensional Data 33%
• Alternating Direction Method of Multipliers 33%
• Computer Vision 33%
• Unified Framework 33%
• Superior Performance 33%
• Object Recognition 33%
• Classification Action 33%
• Dimensional Feature 33%