# Triplet Loss Network for Unsupervised Domain Adaptation
## 3 Architecture and Methodology
### Optimization

Table 5: The best set of hyper-parameters for TripNet for the experiments reported in Table 5. The parameters \(\beta_{Sep}\), \(\beta_{P}\), and \(\beta_{C}\) are the balancing parameters for the triplet loss from Equation (9); \(\lambda_{T}\) and \(\lambda_{S}\) are the balancing parameters between the source and target classification losses from Equation (4); and \(\text{PL}_{\text{Thresh}}\) is the minimum confidence level provided by the classifier so that the image would be considered for pseudo-labeling. ## References

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