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Complex heterogeneity learning: A theoretical and empirical study
Pei Yang, Qi Tan,
Jingrui He
School of Information Sciences
National Center for Supercomputing Applications (NCSA)
Siebel School of Computing and Data Science
Informatics
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Keyphrases
Existing Techniques
100%
Manufacturing Process
100%
Iterative Algorithm
100%
Quality Control
100%
Real-world Application
100%
Nonconvex
100%
Main Idea
100%
Optimization Problem
100%
Task Interdependence
100%
FMRI Analysis
100%
Generalization Performance
100%
Jointly Modeling
100%
Data Heterogeneity
100%
Nonsmooth
100%
Heterogeneous Learning
100%
Bundle Methods
100%
Graphical Approach
100%
Block Coordinate Descent
100%
Task Heterogeneity
100%
Insider Threat Detection
100%
Rademacher Complexity
100%
Instance Correlations
100%
Complex Heterogeneity
100%
Label Consistency
100%
Traffic Prediction
100%
Hybrid Graph
100%
View Consistency
100%
Analysis Quality
100%
Computer Science
Experimental Result
100%
Optimization Problem
100%
Objective Function
100%
Iterative Algorithm
100%
Image Analysis
100%
World Application
100%
Data Heterogeneity
100%
Insider Threat
100%
Threat Detection
100%
Generalization Performance
100%
Traffic Prediction
100%
Mathematics
Objective Function
100%