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Dear Cao Bin:
Glad to see your TrAdaboost project on github, I'm very interested in it!
However, due to my shallow knowledge. I have a little bit of trouble understanding on which pre-trained model the regression model you constructed is based on for transfer learning.Can you use TrAdaBoost_R2 as an example and give me an idea of which pre-trained model he is finetuning on top of?
I hope you take time out of your busy schedule to give me an answer, I would appreciate it!
Best regards
Hangbo Zhu
The text was updated successfully, but these errors were encountered:
Thank you for referencing my open-source project. I would like to clarify that TrAdaboost is an instance transfer strategy proposed by Prof. Yang many years ago, which does not follow the pre-training and fine-tune strategy. The main focus of TrAdaboost is to identify the appropriate weights for the source domain training data in order to reduce the distribution distance between the source and target domains. If you are interested in the pre-training and fine-tune strategy, I recommend looking into parameter-based transfer learning.
Dear Cao Bin:
Glad to see your TrAdaboost project on github, I'm very interested in it!
However, due to my shallow knowledge. I have a little bit of trouble understanding on which pre-trained model the regression model you constructed is based on for transfer learning.Can you use TrAdaBoost_R2 as an example and give me an idea of which pre-trained model he is finetuning on top of?
I hope you take time out of your busy schedule to give me an answer, I would appreciate it!
Best regards
Hangbo Zhu
The text was updated successfully, but these errors were encountered: