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About: PLEASD: A Matlab Toolbox for Structured Learning Changes:Initial Announcement on mloss.org.
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About: An open source Java software providing collaborative filtering algorithms. Changes:Initial Announcement on mloss.org.
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About: Open Source Machine Learning Server Changes:
See release notes - https://predictionio.atlassian.net/secure/ReleaseNote.jspa?projectId=10000&version=11801
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About: Very simple code for training SVMs in the primal. Works particularly well on sparse linear problems. In the non-linear case the entire kernel matrix needs to be computed, so for large problems it is [...] Changes:Initial Announcement on mloss.org.
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About: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi’s quadratic entropy. Instead of minimizing the reconstruction error either based on L2-norm or L1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods. Changes:Initial Announcement on mloss.org.
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About: Hofmann, T. 1999. Probabilistic latent semantic indexing. In Proceedings of the 22nd ACM-SIGIR International Conference on Research and Development in Information Retrieval (Berkeley,Calif.), ACM, New York, 50–57. Changes:Initial Announcement on mloss.org.
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About: A generalized version of spectral clustering using the graph p-Laplacian. Changes:
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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: PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easy-to-use yet still powerful algorithms for machine learning tasks, including a variety of predefined [...] Changes:
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About: pyGPs is a Python package for Gaussian process (GP) regression and classification for machine learning. Changes:Changelog pyGPs v1.3.2December 15th 2014
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