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FIESTA:Fast IdEntification of State of The Art models using adaptive bandit algorithms

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Figure

Figure 1: The left plot shows the distribution of resultswhen varying the data splits and random seeds, withthe dashed lines representing the quartile values
Figure 2: TTTS seeking the optimal model with confi-dence 0.99 from 5 synthetic models
Figure 3: F1 scores for our candidate TDSA models.After 500 evaluations of each model on different datasplits and model seeds we see that the TDLSTM is thestate-of-the-art model.
Table 2: Number of evaluations required to select a TDSA model at a range of confidence levels across 500 runsof TTTS and a standard non-adaptive approach.
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