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Non-Uniform Subset Selection for Active Learning in Structured Data

License: MIT License

Mercury 0.10% MATLAB 42.93% HTML 13.77% Makefile 0.33% Java 9.29% M4 5.81% C 14.86% Python 3.87% C++ 8.87% M 0.16%
activelearning relational-model submodularity scene-recognition object-recognition activity-recognition document-classification

context-active-learning's Introduction

Non-Uniform Subset Selection for Active Learning in Structured Data

Overview

This package is an implementation of the of the paper Non-Uniform Subset Selection for Active Learning in Structured Data, by Sujoy Paul, Jawad Bappy and Amit K Roy-Chowdhury and published at CVPR 2017.

Dependencies

This package uses or depends on the the following package:

  1. Submodular Function Optimization (Used after some modification)
  2. LibSVM (Used unmodified)
  3. Undirected Graphical Model (Used unmodified)

All these packages are included in this package.

Data

This package contains a sample dataset cora.mat which is a processed version of the CORA dataset

Running

Please run the main.m code in order to get results on the cora.mat dataset.

Citation

Please cite the following work if you use this package.

@inproceedings{paul2017non,
  title={Non-uniform subset selection for active learning in structured data},
  author={Paul, Sujoy and Bappy, Jawadul H and Roy-Chowdhury, Amit K},
  booktitle={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages={830--839},
  year={2017},
  organization={IEEE}
}

Contact

Please contact the first author of the associated paper - Sujoy Paul ([email protected]) for any further queries.

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