Tulip Cell
BayesOpt
| Tulip Cell | BayesOpt | |
|---|---|---|
| - | 1 | |
| 32 | 379 | |
| - | - | |
| 0.0 | 1.1 | |
| almost 7 years ago | about 1 year ago | |
| Tcl | C++ | |
| GNU Lesser General Public License v3.0 only | GNU Affero General Public License v3.0 |
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Tulip Cell
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BayesOpt
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The Evolutionary Computation Methods No One Should Use
Very interesting to see how wide spread this is. Stumbled upon it myself by accident when comparing my algorithm to a popular Bayesian optimisation algorithm (https://github.com/rmcantin/bayesopt). Almost every run it would sample the exact centre of the optimisation space. At first I was blown away by the performance until I found it suspicious that the precise optimum was found so often. Shifting the optimum away from the centre greatly reduced the algorithms performance.
What are some alternatives?
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AI-Toolbox - A C++ framework for MDPs and POMDPs with Python bindings
tiny-cnn - header only, dependency-free deep learning framework in C++14
Veles - Distributed machine learning platform
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit