Geometric Clustering and its Applications

Abstract

The AFOSR YIP Grant led to many activities and findings at FSU including the graduation of two PhD students who are now well placed. This report details the activities and findings of our project. The highlights of the achievements include: 1) Design of a new Support Vector Machine algorithm that is linearly convergent and yields an optimal number of support vectors. 2) A fast nearest neighbor algorithm and its optimized implementation in low dimensions. 3) A real time method to compute centers on maps given multiple addresses, when the distance is measured using shortest paths. 4) A 2-clustering algorithm for segments which is a pre-cursor to clustering curves that represent flight paths in air space. 5) A fast Euclidean MST algorithm and its implementation that computes clusterings with max spacing.

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Document Details

Document Type
Technical Report
Publication Date
Oct 31, 2013
Accession Number
ADA592932

Entities

People

  • Piyush Kumar

Organizations

  • Florida State University

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Computer Programming
  • Computer Programs
  • Data Sets
  • Database Management Systems
  • Databases
  • Dimensionality Reduction
  • Geographic Information Systems
  • Geometry
  • Information Systems
  • Programming Languages
  • Python Programming Language
  • Relational Databases
  • Software Development
  • Students
  • Supervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Graph Algorithms and Convex Optimization.
  • Research Science/Academic Research

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Space