CODA uses consensus-based priors and Bayesian updating to select the best candidate model with far fewer labels than prior active model selection methods, beating them on 18 of 26 benchmark tasks.
From detection of individual metastases to classification of lymph node status at the pa- tient level: the camelyon17 challenge
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Consensus-Driven Active Model Selection
CODA uses consensus-based priors and Bayesian updating to select the best candidate model with far fewer labels than prior active model selection methods, beating them on 18 of 26 benchmark tasks.