Deep Kernel Learning

Tags: #machine learning #Deep Kernel Learning

Equation

$$k(x_{i},x_{j}|\phi)=k(h(x_i,w_k),h(x_j,w_k)|w_k,\phi)$$

Latex Code

                                 k(x_{i},x_{j}|\phi)=k(h(x_i,w_k),h(x_j,w_k)|w_k,\phi)
                            

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Introduction

Equation



Latex Code

            k(x_{i},x_{j}|\phi)=k(h(x_i,w_k),h(x_j,w_k)|w_k,\phi)
        

Explanation

The original data instance x_{i} is first mapped to latent space by a non-linear transformation h(x_{i}, w_{k}), usually a deep neural network with parameter w_{k}, and then passed to a kernel function k(x_{i},x_{j}|\phi). See below link Deep Kernel Learning for more details.

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  • Heather Adams
    Yearning for a positive result on this exam.
    2023-11-22 00:00

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    Walter Kelley reply to Heather Adams
    Nice~
    2023-11-30 00:00:00.0

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  • Stephen Carter
    Here's to hoping I pass this exam with ease.
    2023-05-14 00:00

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    Jack Reed reply to Stephen Carter
    Gooood Luck, Man!
    2023-06-04 00:00:00.0

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  • Harry Sanders
    The thought of not passing this exam is haunting me.
    2023-11-21 00:00

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    Scott Phillips reply to Harry Sanders
    You can make it...
    2023-12-13 00:00:00.0

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