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Issue No.03 - July-Sept. (2013 vol.20)
pp: 2-3
John R. Smith , IBM T.J. Watson Research Center
ABSTRACT
Machine learning has become an indispensible tool for the multimedia community. Given large amounts of data, computers using machine learning are able to create rich representations and accomplish impressive discrimination tasks. Yet, the way machines learn is still differs significantly from how humans learn. EIC John R. Smith explains that the way forward is for the multimedia field to create appropriate lesson plans or more generally develop curriculum-based approaches to multimedia machine learning.
INDEX TERMS
Gang Hua, multimedia, multimedia applications, machine learning, learning language models
CITATION
John R. Smith, "Lessons in Learning", IEEE MultiMedia, vol.20, no. 3, pp. 2-3, July-Sept. 2013, doi:10.1109/MMUL.2013.39
REFERENCES
1. J.R. Smith, "Minding the Gap," IEEE MultiMedia, vol. 19, no. 1, 2012, pp. 2–3.
2. J.R. Smith, "Just the Facets," IEEE MultiMedia, vol. 20, no. 1, 2013, pp. 92, 91.
3. G.B. Peterson, "A Day of Great Illumination: B.F. Skinner's Discovery of Shaping," J. Experimental Analysis of Behavior, vol. 82, 2004, pp. 317–328.
4. J.L. Elman, "Learning and Development in Neural Networks: The Importance of Starting Small," Cognition, vol. 48, 1993, pp. 781–799.
5. Y. Bengio et al.," Curriculum Learning," Proc. 26th Ann. Int'l Conf. Machine Learning, ACM, 2009, pp. 41–48.
6. M. Asada et al., "Purposive Behavior Acquisition for a Real Robot by Vision-Based Reinforcement Learning," Machine Learning, vol. 23, nos. 2–3, 1996, pp. 279–303.
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