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Instructions

Build using:

swift build

Example run:

swift run -c release NoisyLabelsExperiments run \
  --dataset weather-sentiment \
  --train-data-portion 0.9 \
  --synthetic-predictors-count 16 \
  --use-synthetic-predictor-features \
  --results-dir temp/results-synthetic

Configurations

For medical-causes and medical-treats we are using LIA configured with the following options:

  • Predictor Embedding Size: 32
  • Instance Hidden Unit Counts: [32, 32, 32, 32]
  • Predictor Hidden Unit Counts: []
  • Confusion Latent Size: 1
  • Gamma: 0.0
  • Entropy Weight: 0.0
  • Use Soft Predictions: true
  • Learning Rate: 1e-4
  • Learning Rate Decay Factor: 1.0
  • Batch Size: 512
  • M Step Count: 1000
  • EM Step Count: 2
  • Marginal Step Count: 1000

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Learning from Noisy Labels

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