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1 : Instance-based transfer learning
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Instance selection (marginal distributions are same while conditional distributions are different) :
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Instance re-weighting (conditional distributions are same while marginal distributions are different) :
2 : Feature-based transfer learning
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Explicit distance:
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case 1 : marginal distributions are same while conditional distributions are different:
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case 1 : conditional distributions are same while marginal distributions are different
JDA
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case 3 : Both marginal distributions and conditional distributions are different
DDA
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Implicit distance :
DANN
3 : Parameter-based transfer learning
- Pretraining + fine tune