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  2. Batch normalization - Wikipedia

    en.wikipedia.org/wiki/Batch_normalization

    In a neural network, batch normalization is achieved through a normalization step that fixes the means and variances of each layer's inputs. Ideally, the normalization would be conducted over the entire training set, but to use this step jointly with stochastic optimization methods, it is impractical to use the global information.

  3. Normalization (machine learning) - Wikipedia

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

    Instance normalization (InstanceNorm), or contrast normalization, is a technique first developed for neural style transfer, and is also only used for CNNs. [26] It can be understood as the LayerNorm for CNN applied once per channel, or equivalently, as group normalization where each group consists of a single channel:

  4. Feature engineering - Wikipedia

    en.wikipedia.org/wiki/Feature_engineering

    Feature engineering in machine learning and statistical modeling involves selecting, creating, transforming, and extracting data features. Key components include feature creation from existing data, transforming and imputing missing or invalid features, reducing data dimensionality through methods like Principal Components Analysis (PCA), Independent Component Analysis (ICA), and Linear ...

  5. Federated learning - Wikipedia

    en.wikipedia.org/wiki/Federated_learning

    Federated averaging (FedAvg) is a generalization of FedSGD, which allows local nodes to perform more than one batch update on local data and exchanges the updated weights rather than the gradients. The rationale behind this generalization is that in FedSGD, if all local nodes start from the same initialization, averaging the gradients is ...

  6. Fourth normal form - Wikipedia

    en.wikipedia.org/wiki/Fourth_normal_form

    Fourth normal form (4NF) is a normal form used in database normalization. Introduced by Ronald Fagin in 1977, 4NF is the next level of normalization after Boyce–Codd normal form (BCNF). Whereas the second , third , and Boyce–Codd normal forms are concerned with functional dependencies , 4NF is concerned with a more general type of ...

  7. Who gets increased Social Security benefits? What to know ...

    www.aol.com/gets-increased-social-security...

    Here's what to know about the recently signed Social Security Fairness Act, including who it will benefit.

  8. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    A residual block in a deep residual network. Here, the residual connection skips two layers. A residual neural network (also referred to as a residual network or ResNet) [1] is a deep learning architecture in which the layers learn residual functions with reference to the layer inputs.

  9. Anxious About Your Holiday Travel Plans? Experts Say These 6 ...

    www.aol.com/anxious-holiday-travel-plans-experts...

    Mental health experts explain the causes and symptoms of travel anxiety, and share 6 tips on how to manage travel anxiety so you can enjoy new experiences more.