Transfer Learning for Bayesian Networks

Luis, Roger; Sucar, L. Enrique; Morales, Eduardo F.

doi:10.1007/978-3-540-88309-8_10

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“…Several of the existing approaches use measures such as those based on entropy [318] or conditional independence [319]. Naturally, the measures obtained from the CP framework (either the non-conformity scores, p-values or the discrepancy measure obtained in the GQBT approach) can be potentially used in transfer learning contexts.…”

Section: Other Possible Directionsmentioning

confidence: 99%

Conformal predictions in multimedia pattern recognition

Balasubramanian¹

2011

SIGMultimedia Rec.

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The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. like a bird', in his words). I cannot thank him enough for his strong belief in me over the years, for setting standards of excellence that will take me a lifetime to scale, for housing me in an environment suffused with bright minds and numerous opportunities for exposure and growth, and most importantly, for his never-failing support through every high and low of my PhD.

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Section: Other Possible Directionsmentioning

confidence: 99%

Conformal predictions in multimedia pattern recognition

Balasubramanian¹

2011

SIGMultimedia Rec.

View full text Add to dashboard Cite

show abstract

Transfer Learning for Bayesian Networks

Cited by 1 publication

References 4 publications

Conformal predictions in multimedia pattern recognition

Conformal predictions in multimedia pattern recognition

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