Closed apoorvagnihotri closed 4 years ago
Abstract
Mining Gold!
Active Learning
Bayesian Optimization
Formalizing Bayesian Optimization
Acquisition Functions
Probability of Improvement (PI)
Expected Improvement (EI)
PI vs. EI
Thompson Sampling
Random
Summary of Acquisition Functions
Other Acq. Functions
Comparison
Why is it beneficial to optimize the acquisition function?
Hyperparameter Tuning
Example 1, 2, 3
Conclusion and Summary
Embrace Bayesian Optimization
Acknowledgements
Further Reading
fig.text
Abstract
+Mining Gold!
1024eb51945b83b8e000ae7b98687c48620e46d4 91e2e1a32e9eb48ddecd842fea6024b829ccc679Active Learning
5539934c3cd56e134a67de16d194a4d8081f3a32Bayesian Optimization
+Formalizing Bayesian Optimization
6e40a36d858e4100eb525c1e1572834737bc6663Acquisition Functions
4b6d52cf2d43a709ce83f270e76dbdcbb51aea24Probability of Improvement (PI)
3df731b316e06674dadb520e28fde13bedd1b450Expected Improvement (EI)
010cd004d9ac5e319eaf6c3d25faf38d0581c2e3PI vs. EI
87ac6d5434118ca8acdfe0fc57a63b0c791b92c1Thompson Sampling
5abe99b5c3d5f3137e1d677514c75d1d64d5da45Random
+Summary of Acquisition Functions
Other Acq. Functions
0be836f40ae1fd71daa53aa42c46beb04fed15eeComparison
+Why is it beneficial to optimize the acquisition function?
Hyperparameter Tuning
cb5b009751da86b3b5b2d95005726077b0e5cd77Example 1, 2, 3
629fa365fe66da3217f034d7463ba429ed37e368Conclusion and Summary
+Embrace Bayesian Optimization
Acknowledgements
Further Reading
fig.text
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