Skip to main content
SpringerLink
Log in

Active Learning—What, When, and Where to Deploy?

  • Chapter
  • First Online:
Active Learning to Minimize the Possible Risk of Future Epidemics

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSINTELL))

  • 42 Accesses

Abstract

The journey of human learning is characterized by its gradual and extended nature, involving years of education in schools and universities to attain expertise in specific domains.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Weiss K, Khoshgoftaar TM, Wang D (2016) A survey of transfer learning. J Big data 3(1):1–40

    Article  Google Scholar 

  2. Anzai Y, Simon HA (1979) The theory of learning by doing. Psychol Rev 86(2):124

    Article  Google Scholar 

  3. Jordan MI, Mitchell TM (2015) Machine learning: trends, perspectives, and prospects. Science 349(6245):255–260

    Article  MathSciNet  MATH  Google Scholar 

  4. Simon HA (1983) Why should machines learn? In: Machine learning, pp 25–37. Morgan Kaufmann

    Google Scholar 

  5. Sammut C, Webb GI (eds) (2011) Encyclopedia of machine learning. Springer Science & Business Media

    Google Scholar 

  6. Angluin D (1988) Queries and concept learning. Mach Learn 2:319–342

    Article  MathSciNet  MATH  Google Scholar 

  7. Settles B (2009) Active learning literature survey

    Google Scholar 

  8. Cohn D, Atlas L, Ladner R (1994) Improving generalization with active learning. Mach Learn 15:201–221

    Article  Google Scholar 

  9. Lewis D, Gale W (1994) A sequential algorithm for training text classifiers. In: Proceedings of the ACM SIGIR conference on research and development in information retrieval, pp 3–12. ACM/Springer

    Google Scholar 

  10. Seung HS, Opper M, Sompolinsky H (1992) Query by committee. In: Proceedings of the ACM workshop on computational learning theory, pp 287–294

    Google Scholar 

  11. Bouguelia MR, Nowaczyk S, Santosh KC, Verikas A (2018) Agreeing to disagree: Active learning with noisy labels without crowdsourcing. Int J Mach Learn Cybern 9:1307–1319

    Google Scholar 

  12. Roy N, McCallum A (2001) Toward optimal active learning through sampling estimation of error reduction. In: Proceedings of the international conference on machine learning (ICML), pp 441–448. Morgan Kaufmann

    Google Scholar 

  13. Cohn D, Ghahramani Z, Jordan MI (1996) Active learning with statistical models. J Artif Intell Res 4:129–145

    Article  MATH  Google Scholar 

  14. Geman S, Bienenstock E, Doursat R (1992) Neural networks and the bias/variance dilemma. Neural Comput 4(1):1–58

    Article  Google Scholar 

  15. Settles B, Craven M (2008) An analysis of active learning strategies for sequence labeling tasks. In: Proceedings of the conference on empirical methods in natural language processing (EMNLP), pp 1069–1078. ACL Press

    Google Scholar 

  16. Nakarmi S, Santosh KC (2023) Active Learning to Minimize the Risk from Future Epidemics. In: IEEE conference on artificial intelligence (CAI). IEEE

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Applied AI Research Lab, Department of Computer Science, University of South Dakota, Vermillion, USA

    KC Santosh & Suprim Nakarmi

Authors
  1. KC Santosh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Suprim Nakarmi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to KC Santosh .

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Santosh, K., Nakarmi, S. (2023). Active Learning—What, When, and Where to Deploy?. In: Active Learning to Minimize the Possible Risk of Future Epidemics. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-99-7442-9_2

Download citation

Publish with us

Policies and ethics

Search

Navigation