Subquadratic approximation algorithms for clustering problems in high dimensional spaces

Keyphrases

• Approximation Algorithms 100%
• High-dimensional Space 100%
• Clustering Problem 100%
• Subquadratic 100%
• Clustering Rule 100%
• Cluster-based 50%
• Statistical Analysis 50%
• Computer Vision 50%
• Pattern Recognition 50%
• Approximate Solution 50%
• Distributed Protocol 50%
• Search Engine 50%
• Analysis Patterns 50%
• Number of Data 50%
• Distance Measure 50%
• Natural Clustering 50%
• Computational Biology 50%
• Minimum Spanning Tree 50%
• Information Retrieval 50%
• Geographic Analysis 50%
• Cluster Solutions 50%
• Approximation Parameters 50%
• Agglomerative Clustering 50%
• Data Classification 50%
• Alta 50%
• Retrieval Data 50%
• Sparse Partition 50%

Computer Science

• Approximation Algorithms 100%
• High Dimensional Space 100%
• Approximation (Algorithm) 50%
• Data Mining 50%
• Distributed Protocol 50%
• Search Engine 50%
• Approximate Solution 50%
• Analysis Pattern 50%
• Agglomerative Clustering 50%
• Sparse Partition 50%
• Information Retrieval 50%
• Computer Vision 50%
• Minimum Spanning Tree 50%
• Pattern Recognition 50%

Mathematics

• Running Time 100%
• Clustering 100%
• Data Point 100%
• Dimensional Space 100%
• Approximates 50%
• Approximate Solution 50%
• Minimum Spanning Tree 50%
• Computer Statistical Analysis 50%
• Data Mining 50%