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Keep the gradient flowing

Policy Gradients Part 1: The REINFORCE Estimator On the Link Between Optimization and Polynomials, Part 6. Optimization Nuggets: Stochastic Polyak Step-size, Part 2 Optimization Nuggets: Stochastic Polyak Step-size On the Convergence of the Unadjusted Langevin Algorithm The Russian Roulette: An Unbiased Estimator of the Limit Notes on the Frank-Wolfe Algorithm, Part III: backtracking line-search On the Link Between Optimization and Polynomials, Part 5 Optimization Nuggets: Implicit Bias of Gradient-based Methods Optimization Nuggets: Exponential Convergence of SGD On the Link Between Optimization and Polynomials, Part 4 On the Link Between Optimization and Polynomials, Part 3 On the Link Between Optimization and Polynomials, Part 2 On the Link Between Polynomials and Optimization, Part 1 How to Evaluate the Logistic Loss and not NaN trying Notes on the Frank-Wolfe Algorithm, Part II: A Primal-dual Analysis Three Operator Splitting Notes on the Frank-Wolfe Algorithm, Part I Optimization inequalities cheatsheet A fully asynchronous variant of the SAGA algorithm Hyperparameter optimization with approximate gradient Lightning v0.1 scikit-learn-contrib, an umbrella for scikit-learn related projects. SAGA algorithm in the lightning library On the consistency of ordinal regression methods Holdout cross-validation generator IPython/Jupyter notebook gallery PyData Paris - April 2015 Data-driven hemodynamic response function estimation Plot memory usage as a function of time
scikit-learn 0.9
Fabian Pedregosa · 2011-10-02 · via Keep the gradient flowing

Last week we released a new version of scikit-learn. The Changelog is particularly impressive, yet personally this release is important for other reasons. This will probably be my last release as a paid engineer. I'm starting a PhD next month, and although I plan to continue contributing to the project and make a few more releases, I will certainly have less time to devote to it. Luckily, I received a lot of help from the community while preparing the release, from Changelog writing to build of Windows binaries, thus I expect the transition to go smoothly. Almost two years have elapsed since the first 0.1 release. During this time, we did a lot of refactoring and broke the API several times. However, I've seen some concerns about API stability both at the EuroScipy conference and in the mailing list where I’ve realized we need to provide an API that does not break in every release, and do this in a way that the project remains fun for developers. That's why I'm extremely glad to see that although this release is big in changes, these have been made in a more organized manner. Yes, we've broken the API once again, but now there's a compatibility layer that ensures that code written for 0.8 will continue working with the new release.