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A Mathematical Analysis of Learning Loss for Active Learning in Regression.
CVPR Workshops, pp.3320-3328, (2021)
Active learning continues to remain significant in the industry since it is data efficient. Not only is it cost effective on a constrained budget, continuous refinement of the model allows for early detection and resolution of failure scenarios during the model development stage. Identifying and fixing failures with the model is crucial...More
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