Description

Book Synopsis

.- Theory of Neural Networks and Machine Learning.

.- Multi-label Robust Feature Selection via Subspace-Sparsity Learning.

.- Nullspace-based metric for classification of dynamical systems and sensors.

.- On the Bayesian Interpretation of Robust Regression Neural Networks.

.- Probability-Generating Function Kernels for Spherical Data.

.- Tailored Finite Point Operator Networks for Interface problems.

.- Novel Methods in Machine Learning.

.- A Simple Task-aware Contrastive Local Descriptor Selection Strategy for Few-shot Learning between inter class and intra class.

.- Adaptive Compression of the Latent Space in Variational Autoencoders.

.- Asymmetric Isomap for Dimensionality Reduction and Data Visualization.

.- CALICO: Confident Active Learning with Integrated Calibration.

.- Improved Multi-hop Reasoning through Sampling and Aggr

Artificial Neural Networks and Machine Learning

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    £64.99

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    Order before 4pm tomorrow for delivery by Sat 27 Jun 2026.

    A Paperback by Michael Wand

    15 in stock

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      View other formats and editions of Artificial Neural Networks and Machine Learning by Michael Wand

      Publisher: Springer
      Publication Date: 9/17/2024
      ISBN13: 9783031723315, 978-3031723315
      ISBN10: 3031723317

      Description

      Book Synopsis

      .- Theory of Neural Networks and Machine Learning.

      .- Multi-label Robust Feature Selection via Subspace-Sparsity Learning.

      .- Nullspace-based metric for classification of dynamical systems and sensors.

      .- On the Bayesian Interpretation of Robust Regression Neural Networks.

      .- Probability-Generating Function Kernels for Spherical Data.

      .- Tailored Finite Point Operator Networks for Interface problems.

      .- Novel Methods in Machine Learning.

      .- A Simple Task-aware Contrastive Local Descriptor Selection Strategy for Few-shot Learning between inter class and intra class.

      .- Adaptive Compression of the Latent Space in Variational Autoencoders.

      .- Asymmetric Isomap for Dimensionality Reduction and Data Visualization.

      .- CALICO: Confident Active Learning with Integrated Calibration.

      .- Improved Multi-hop Reasoning through Sampling and Aggr

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