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2
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Consistent Nonparametric Tests of Independence
– Arthur Gretton, László Györfi, Arthur Gretton, László Györfi
- 2009
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19
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Kernel dimension reduction in regression
– Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
- 2006
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2
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Kernel Bayes ’ Rule
– Kenji Fukumizu, Le Song, Arthur Gretton
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6
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Hilbert Space Embeddings and Metrics on Probability Measures
– Bharath K. Sriperumbudur, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet, Ingo Steinwart
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DISCUSSION OF: BROWNIAN DISTANCE COVARIANCE
– Arthur Gretton, Kenji Fukumizu, Bharath K
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9
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Characteristic Kernels on Groups and Semigroups
– Kenji Fukumizu, Arthur Gretton, Bharath Sriperumbudur, Bernhard Schölkopf
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KERNEL DIMENSION REDUCTION IN REGRESSION 1
– Kenji Fukumizu, Francis R. Bach, Michael, I. Jordan
|
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1
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Brisk Kernel ICA
– Stefanie Jegelka, Arthur Gretton
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25
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A kernel statistical test of independence
– Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alexander J. Smola
- 2008
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12
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Statistical consistency of kernel canonical correlation analysis
– Kenji Fukumizu, Francis R. Bach, Arthur Gretton
- 2007
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2
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Nonparametric Tree Graphical Models via Kernel Embeddings
– Le Song, Arthur Gretton, Carlos Guestrin
|
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2
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Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation
– Taiji Suzuki, Masashi Sugiyama
|
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3
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A Kernel-based Causal Learning Algorithm
– Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf
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3
|
Fast kernel-based independent component analysis
– Hao Shen, Stefanie Jegelka, Arthur Gretton
|
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20
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A kernel method for the two sample problem
– Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, Alexander Smola
- 2007
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4
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Nonparametric independence tests: Space partitioning and kernel approaches
– Arthur Gretton, László Györfi
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2
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A.: Fast kernel ICA using an approximate newton method
– Hao Shen, Stefanie Jegelka, Arthur Gretton
- 2007
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27
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A Hilbert space embedding for distributions
– Alex Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
- 2007
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Introduction to Machine Learning
– Bernhard Schölkopf
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