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  2. File:Multiheaded attention, block diagram.png - Wikipedia

    en.wikipedia.org/wiki/File:Multiheaded_attention...

    Multiheaded_attention,_block_diagram.png (656 × 600 pixels, file size: 32 KB, MIME type: image/png) This is a file from the Wikimedia Commons . Information from its description page there is shown below.

  3. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Multi-head attention enhances this process by introducing multiple parallel attention heads. Each attention head learns different linear projections of the Q, K, and V matrices. This allows the model to capture different aspects of the relationships between words in the sequence simultaneously, rather than focusing on a single aspect.

  4. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    Concretely, let the multiple attention heads be indexed by , then we have (,,) = [] ((,,)) where the matrix is the concatenation of word embeddings, and the matrices ,, are "projection matrices" owned by individual attention head , and is a final projection matrix owned by the whole multi-headed attention head.

  5. For Dummies - Wikipedia

    en.wikipedia.org/wiki/For_Dummies

    Notable For Dummies books include: DOS For Dummies, the first, published in 1991, whose first printing was just 7,500 copies [4] [5] Windows for Dummies, asserted to be the best-selling computer book of all time, with more than 15 million sold [4] L'Histoire de France Pour Les Nuls, the top-selling non-English For Dummies title, with more than ...

  6. Head First (book series) - Wikipedia

    en.wikipedia.org/wiki/Head_First_(book_series)

    Head First is a series of introductory instructional books to many topics, published by O'Reilly Media. It stresses an unorthodox, visually intensive, reader-involving combination of puzzles , jokes , nonstandard design and layout, and an engaging, conversational style to immerse the reader in a given topic.

  7. Feature integration theory - Wikipedia

    en.wikipedia.org/wiki/Feature_integration_theory

    Feature integration theory is a theory of attention developed in 1980 by Anne Treisman and Garry Gelade that suggests that when perceiving a stimulus, features are "registered early, automatically, and in parallel, while objects are identified separately" and at a later stage in processing.

  8. Broadbent's filter model of attention - Wikipedia

    en.wikipedia.org/wiki/Broadbent's_filter_model_of...

    Additional research proposes the notion of a moveable filter. The multimode theory of attention combines physical and semantic inputs into one theory. Within this model, attention is assumed to be flexible, allowing different depths of perceptual analysis. [28] Which feature gathers awareness is dependent upon the person's needs at the time. [3]

  9. Binding problem - Wikipedia

    en.wikipedia.org/wiki/Binding_problem

    The consciousness and binding problem is the problem of how objects, background, and abstract or emotional features are combined into a single experience. [1] The binding problem refers to the overall encoding of our brain circuits for the combination of decisions, actions, and perception.