About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier. Changes:
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About: A Matlab script for learning vector-valued functions and kernels on the output space. Changes:Added code for learning low-rank output kernels.
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About: This package is a set of Matlab scripts that implements the algorithms described in the submitted paper: "Lp-Lq Sparse Linear and Sparse Multiple Kernel MultiTask Learning". Changes:Initial Announcement on mloss.org.
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About: PSVM - Support vector classification, regression and feature extraction for non-square dyadic data, non-Mercer kernels. Changes:Initial Announcement on mloss.org.
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About: OpenKernel is a library for creating, combining, learning and using kernels for machine learning applications. Changes:Initial Announcement on mloss.org.
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About: This software is designed for learning translation invariant kernels for classification with support vector machines. Changes:Initial Announcement on mloss.org.
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