論文紹介 semi-supervised learning with deep generative models

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紹介 Semisupervised Learning with Deep Generative Models NIPS2014読み会 @ 東, 2015/01/20 Preferred Networks, 得居 誠也 @beam2d

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  • Semi-supervised Learning

    with Deep Generative ModelsNIPS2014 @ , 2015/01/20

    Preferred Networks,

    @beam2d

  • l

    l

    (semi-supervised learning)

    2

  • 4

    3

    Transductive SVM

    Manifold Tangent Classifier (MTC), AtlasRBF

  • MNIST 100 3.33%

    SVHN NORB

    4

  • 5

    x

    z

    p(x, z) = p(z)p(x|z)

  • M1

    6

    Neural Net

    z N (z;0, I)

    (,)

    x N (x|, diag2)

  • M1

    7

    Neural Net

    z N (z;0, I)

    x Bernoulli(x|)

    Gaussian Bernoulli

  • M2Gaussian

    8

    Neural Net

    z N (z;0, I)

    (,)

    y Cat(y|)

    x N (x|, diag2)

  • AutoEncoder

    l

    l NN

    9

    p(z)p(x|z) x z

    p(z)p(x|z) q(x)q(z|x)

    z

    x

    NN( ) NN( )

    q(x)

  • NN

    10

    l M1

    l M2

    q(z|x) = N (z|(x), diag2(x)).NN

    NN

    q(z|y,x) = N (z|(y,x), diag2(y,x)),q(y|x) = Cat(y|(x)).

  • M1 AutoEncoder

    11

    log p(x) Eq(z|x)[log p(x|z)]KL[q(z|x)p(z)]

    q(x, z) = p(x, z)

    TSVM M2

    z q(z|x)

    AutoEncoder z

  • M2

    12

    log p(x, y) L(x, y) :=Eq(z|x,y)[log p(x|y, z) + log p(y) + log p(z) log q(z|x, y)]

    log p(x) U(x) :=Eq(y,z|x)[log p(x|y, z) + log p(y) + log p(z) log q(y, z|x)]

    (x,y):labeled

    L(x, y) +

    x:unlabaled

    U(x)

    (x,y):labeled

    log q(y|x)

    q(y|x)

  • SGVB (SBP)

    l

    l

    l Gaussian

    Stochastic Gradient Variational Bayes Stochastic BackProp ICLR14, ICML14

    13

    Eq(z|x,y)Eq(z|x,y)[f(x, y, z)]

    Eq(z|x,y)[f(x, y, z)] = EN (|0,I)[f(x, y,(x) + (x) )]

    Eq(z|x,y)[f(x, y, z)] = EN (|0,I)[f(x, y,(x) + (x) )]

  • SGVB(SBP) +

    l OK

    l AdaGrad RMSprop

    3.2 4.4 4.4

    14

  • 2 2

    l (MNIST, SVHN, NORB)

    l 2

    2 (MNIST)

    (MNIST, SVHN)

    15

    z zyx|y, zy x|y, zx

    z|x

  • %

    16

  • 17

    2 (style)

    zz

  • 18

    10

    zx|y, z

  • l

    l

    l

    l DBM NN

    l DBM

    l

    19

  • Kingma, D. P., Mohamed, S., Jimenez Rezende, D., & Welling, M. (2014). Semi-supervised Learning with Deep Generative Models. In Advances in Neural Information Processing Systems 27 (pp. 35813589).

    Stochastic Gradient VB AutoEncoder

    Kingma, D. P., & Welling, M. (2014). Auto-Encoding Variational Bayes.International Conference on Learning Representations.

    Stochastic BackProp

    Rezende, D. J., Mohamed, S., & Wierstra, D. (2014). Stochastic Backpropagation and Approximate Inference in Deep Generative Models. In Proceedings of the 31st International Conference on Machine Learning (pp. 12781286).

    20