Second Generation of Mass Estimation

Abstract

Three progresses were made in the field through mass estimation: (1) the first adaptive version of mass estimation using a new nearest neighbor procedure which runs significantly faster than existing nearest neighbor procedures and needs no indexing schemes, (2) the first mass-based Bayesian classifier which estimates the likelihood directly in multi-dimensional space; unlike existing Bayesian classifiers which estimate simplified surrogates of likelihood (e.g., one-dimensional likelihood), and (3) the first mass-based similarity measure which can be an effective alternative to distance-based similarity measure.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2013
Accession Number
ADA590623

Entities

People

  • Kai M. Ting

Organizations

  • Monash University

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Anomaly Detection
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Bayesian Networks
  • Change Detection
  • Computational Science
  • Computer Science
  • Data Mining
  • Databases
  • Dimensionality Reduction
  • Information Retrieval
  • Information Science
  • Kernel Functions
  • Machine Learning
  • Network Science
  • Supervised Machine Learning
  • Two Dimensional

Readers

  • Computational Fluid Dynamics (CFD)
  • Inertial Navigation Systems.
  • Regression Analysis.

Technology Areas

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