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@yorkerlin
yorkerlin committed Feb 9, 2016
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- Added optimisation of inducing variables in sparse GP inference [Wu Lin].
- Added optimisation methods for GP inference (Newton, Cholesky, LBFGS, ...) [Wu Lin].
- Added Automatic Relevance Determination (ARD) kernel functionality for variational GP inference [Wu Lin].
- Added BFGS based optimisation for GP inference [Wu Lin].
- Updated Notebook for variational GP inference [Wu Lin].
- New framework for stochastic optimisation (l1/2 loss, mirror descent, proximal gradients, adagrad, SVRG, RMSProp, adadelta, ...) [Wu Lin].
- New Shogun meta-language for automatically generating code listings in all target languages [Esben Sörig].
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2 comments on commit 83031f7

@karlnapf
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too late, it is released ;)

@yorkerlin
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Never mind :)
I will add more features in the GP module this year. (eg, Andrew's work and our method)

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