Greedy Algorithm

Authors

  • Abhishek Jain CSE Department, MD UNIVERSITY (Dronacharya College of Engineering), Gurgaon
  • Manjeet Saini CSE Department, MD UNIVERSITY (Dronacharya College of Engineering), Gurgaon
  • Manohar Kumar CSE Department, MD UNIVERSITY (Dronacharya College of Engineering), Gurgaon

DOI:

https://doi.org/10.53555/nncse.v2i4.451

Keywords:

Greedy, Huffman, activity, optimal algorithm

Abstract

This paper describes the basic technological aspects of algorithm, algorithmic efficiency and Greedy algorithm. Algorithmic efficiency is the property of an algorithm which relate to the amount of resources use by the algorithm in computer sciences. An algorithm is considered efficient if its resource consumption (or computational cost) is at or below some acceptable level.

References

Algorithms Design and Analysis by Udit Agarwal

A.R. Barron. Universal approximation bounds for superpositions of a sigmoidal function. IEEE Transactions on Information Theory, 39(3):930–945, 1993.

Y. Freund and R.E. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci., 55(1):119–139, 1997.

Jerome Friedman, Trevor Hastie, and Robert Tibshirani. Additive logistic regression: A statistical view of boosting. The Annals of Statistics, 28(2):337–407, 2000. With discussion.

T. J. Hastie and R. J. Tibshirani. Generalized additive models. Chapman and Hall Ltd., London, 1990.

Downloads

Published

2015-04-30

How to Cite

Jain, A., Saini, M., & Kumar, M. (2015). Greedy Algorithm. Journal of Advance Research in Computer Science & Engineering (ISSN 2456-3552), 2(4), 12-15. https://doi.org/10.53555/nncse.v2i4.451