A kernel two-sample test

Arthur Gretton; Karsten Borgwardt; Malte J. Rasch; Bernhard Schölkopf; Alexander J. Smola

doi:https://doi.org/10.5555/2188385.2188410

A kernel two-sample test

2012 · MPG.PuRe (Max Planck Society) · 2,224 citations · 3 from inside this corpus

Arthur Gretton, Karsten Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

11 of 11 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.

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Citation edge evidence

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Learning Transferable Features with Deep Adaptation Networks→A kernel two-sample testLegacy edge — source detail unavailable
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks→A kernel two-sample testLegacy edge — source detail unavailable
Adversarial Examples Are Not Easily Detected→A kernel two-sample testLegacy edge — source detail unavailable
A kernel two-sample test→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
A kernel two-sample test→Estimating the Support of a High-Dimensional DistributionLegacy edge — source detail unavailable
A kernel two-sample test→Rademacher and Gaussian Complexities: Risk Bounds and Structural ResultsLegacy edge — source detail unavailable
A kernel two-sample test→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
A kernel two-sample test→A Kernel Method for the Two-Sample-ProblemLegacy edge — source detail unavailable
A kernel two-sample test→A Class of Statistics with Asymptotically Normal DistributionLegacy edge — source detail unavailable
A kernel two-sample test→Using the Nyström Method to Speed Up Kernel MachinesLegacy edge — source detail unavailable
A kernel two-sample test→Support Vector MachinesLegacy edge — source detail unavailable
A Kernel Method for the Two-Sample-Problem→A Class of Statistics with Asymptotically Normal DistributionLegacy edge — source detail unavailable
A Kernel Method for the Two-Sample-Problem→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
A Kernel Method for the Two-Sample-Problem→Using the Nyström Method to Speed Up Kernel MachinesLegacy edge — source detail unavailable
A Kernel Method for the Two-Sample-Problem→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
A Kernel Method for the Two-Sample-Problem→Estimating the Support of a High-Dimensional DistributionLegacy edge — source detail unavailable
A Kernel Method for the Two-Sample-Problem→Rademacher and Gaussian Complexities: Risk Bounds and Structural ResultsLegacy edge — source detail unavailable
Learning Transferable Features with Deep Adaptation Networks→Analysis of Representations for Domain AdaptationLegacy edge — source detail unavailable
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks→Learning Transferable Features with Deep Adaptation NetworksLegacy edge — source detail unavailable

What this paper cites, inside the corpus

Paper	Year	Cited
UCI Repository of machine learning databases	1998	10,546
Estimating the Support of a High-Dimensional Distribution	2001	6,097
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results	2001	2,126
Analysis of Representations for Domain Adaptation	2007	2,044
A Kernel Method for the Two-Sample-Problem	2007	1,949
A Class of Statistics with Asymptotically Normal Distribution	1992	1,913
Using the Nyström Method to Speed Up Kernel Machines	2000	1,519
Support Vector Machines	2020	1,484

What cites it, inside the corpus

Paper	Year	Cited
Learning Transferable Features with Deep Adaptation Networks	2015	2,839
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks	2017	1,634
Adversarial Examples Are Not Easily Detected	2017	1,428

Links

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Topics

Bayesian Modeling and Causal Inference	Computer Science
Statistical Methods and Inference	Mathematics
Bayesian Methods and Mixture Models	Computer Science

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complete

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supports5 author record(s) attached.
supports94 reference(s) recorded.
neutralThe DOI carries no year to check against.
supportsA title is present.

Provenance

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