Kristin Bennett

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isabelle@clopinetcom Report prepared by Isabelle Guyon with information from the data donors listed below: Chemo-informatics (HIVA and C datasets): The National Cancer Institute (USA) provide the data used in the HIVA dataset. Text processing (NOVA and D datasets):-Tom Mitchell (USA) and Ron Bekkerman (Israel) provided the data used in the NOVA and D(More)
—ChaLearn is organizing for IJCNN 2015 an Automatic Machine Learning challenge (AutoML) to solve classification and regression problems from given feature representations, without any human intervention. This is a challenge with code submission: the code submitted can be executed automatically on the challenge servers to train and test learning machines on(More)
Copyright and reuse: The Warwick Research Archive Portal (WRAP) makes this work of researchers of the University of Warwick available open access under the following conditions. This article is made available under the Creative Commons Attribution-3.0 Unported (CC BY 3.0) license and may be reused according to the conditions of the license. For more details(More)
ChaLearn is organizing the Automatic Machine Learning (AutoML) contest 2015, which challenges participants to solve classication and regression problems without any human intervention. Participants' code is automatically run on the contest servers to train and test learning machines. However, there is no obligation to submit code; half of the prizes can be(More)
A procedure to obtain all components of the elastic-strain tensor by simultaneous Rietveld refinement of diffraction patterns collected at different specimen orientations is described. The refined lattice parameters yield the hydrostatic strain component. If the lattice constants of the unstrained reference specimen are not known, the deviatoric strain(More)
The AutoML Challenge is designed to promote research on reducing or removing the need for human interaction in applying machine learning (ML) to practical problems. This refers to all aspects of automating the ML process beyond model selection, hyper-parameter optimization , and model search. Automation is desired for data loading and formatting, detection(More)
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