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  2. Batch normalization - Wikipedia

    en.wikipedia.org/wiki/Batch_normalization

    The explanation made in the original paper [1] was that batch norm works by reducing internal covariate shift, but this has been challenged by more recent work. One experiment [2] trained a VGG-16 network [5] under 3 different training regimes: standard (no batch norm), batch norm, and batch norm with noise added to each layer during training ...

  3. Normalization (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(machine...

    Adaptive instance normalization (AdaIN) is a variant of instance normalization, designed specifically for neural style transfer with CNNs, rather than just CNNs in general. [ 27 ] In the AdaIN method of style transfer, we take a CNN and two input images, one for content and one for style .

  4. Instance-based learning - Wikipedia

    en.wikipedia.org/wiki/Instance-based_learning

    It is called instance-based because it constructs hypotheses directly from the training instances themselves. [3] This means that the hypothesis complexity can grow with the data: [3] in the worst case, a hypothesis is a list of n training items and the computational complexity of classifying a single new instance is O(n). One advantage that ...

  5. Online machine learning - Wikipedia

    en.wikipedia.org/wiki/Online_machine_learning

    In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once.

  6. Ensemble learning - Wikipedia

    en.wikipedia.org/wiki/Ensemble_learning

    The Euclidean distance is used as the metric to measure both the performance of a single classifier or regressor (the distance between its point and the ideal point) and the dissimilarity between two classifiers or regressors (the distance between their respective points). This perspective transforms ensemble learning into a deterministic problem.

  7. Local landmarks lost and damaged by raging Los Angeles fires

    www.aol.com/iconic-landmarks-lost-damaged-raging...

    The Reel Inn, one of the Pacific Coast Highway's most iconic landmarks, burned in the fires, according to a GoFundMe page shared by the restaurant's social media and its owners.

  8. Instance selection - Wikipedia

    en.wikipedia.org/wiki/Instance_selection

    Approaches for instance selection can be applied for reducing the original dataset to a manageable volume, leading to a reduction of the computational resources that are necessary for performing the learning process. Algorithms of instance selection can also be applied for removing noisy instances, before applying learning algorithms.

  9. 18 New Anti-Inflammatory Recipes to Make in January - AOL

    www.aol.com/18-anti-inflammatory-recipes-january...

    Salmon is rich in omega-3 fatty acids, while the beans provide a nice texture and are a great source of fiber. A quick soy-sesame-ginger dressing completes this salad, perfect for lunch or dinner. ...