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  2. MindSpore - Wikipedia

    en.wikipedia.org/wiki/MindSpore

    Download as PDF; Printable version; In other projects ... Feature learning; Learning to rank; Grammar induction; ... MindSpore is a open-source software framework for ...

  3. File:RelativeRankLearning2.pdf - Wikipedia

    en.wikipedia.org/wiki/File:RelativeRankLearning2.pdf

    English: Learning in the partial-information sequential search paradigm. The numbers display the expected values of applicants based on their relative rank (out of m total applicants seen so far) at various points in the search. Expectations are calculated based on the case when their values are uniformly distributed between 0 and 1.

  4. Learning to rank - Wikipedia

    en.wikipedia.org/wiki/Learning_to_rank

    Learning to rank [1] or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. [2]

  5. Ranking SVM - Wikipedia

    en.wikipedia.org/wiki/Ranking_SVM

    In machine learning, a ranking SVM is a variant of the support vector machine algorithm, which is used to solve certain ranking problems (via learning to rank). The ranking SVM algorithm was published by Thorsten Joachims in 2002. [1] The original purpose of the algorithm was to improve the performance of an internet search engine.

  6. Relevance vector machine - Wikipedia

    en.wikipedia.org/wiki/Relevance_vector_machine

    In mathematics, a Relevance Vector Machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and probabilistic classification. [1] A greedy optimisation procedure and thus fast version were subsequently developed.

  7. 12 reasons you aren't losing weight even though you're eating ...

    www.aol.com/lifestyle/12-reasons-arent-losing...

    You've heard it a million times: Eat fewer calories, lose weight. But what if you're in a calorie deficit—consuming fewer calories than you're burning—and still not losing?

  8. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce ...

  9. Caffe (software) - Wikipedia

    en.wikipedia.org/wiki/Caffe_(software)

    Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, originally developed at University of California, Berkeley. It is open source , under a BSD license . [ 4 ]