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Volumn , Issue , 2017, Pages

Revisiting classifier two-sample tests

Author keywords

[No Author keywords available]

Indexed keywords

STATISTICAL TESTS;

EID: 85063956288     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (195)

References (56)
  • 1
    • 2142645905 scopus 로고    scopus 로고
    • Effect of high dimension: By an example of a two sample problem
    • Z. Bai and H. Saranadasa. Effect of high dimension: by an example of a two sample problem. Statistica Sinica, 1996.
    • (1996) Statistica Sinica
    • Bai, Z.1    Saranadasa, H.2
  • 4
    • 0001135785 scopus 로고
    • Sampling and bayes' inference in scientific modelling and robustness
    • G. E. P. Box. Sampling and bayes' inference in scientific modelling and robustness. Journal of the Royal Statistical Society, 1980.
    • (1980) Journal of the Royal Statistical Society
    • Box, G.E.P.1
  • 5
    • 84965171796 scopus 로고    scopus 로고
    • Fast two-sample testing with analytic representations of probability measures
    • K. P. Chwialkowski, A. Ramdas, D. Sejdinovic, and A. Gretton. Fast two-sample testing with analytic representations of probability measures. NIPS, 2015.
    • (2015) NIPS
    • Chwialkowski, K.P.1    Ramdas, A.2    Sejdinovic, D.3    Gretton, A.4
  • 6
    • 84983185824 scopus 로고    scopus 로고
    • Training generative neural networks via Maximum Mean Discrepancy optimization
    • K. G. Dziugaite, D. M. Roy, and Z. Ghahramani. Training generative neural networks via Maximum Mean Discrepancy optimization. UAI, 2015.
    • (2015) UAI
    • Dziugaite, K.G.1    Roy, D.M.2    Ghahramani, Z.3
  • 7
    • 0003014023 scopus 로고
    • Binomial approximation to the poisson binomial distribution
    • W. Ehm. Binomial approximation to the poisson binomial distribution. Statistics & Probability Letters, 1991.
    • (1991) Statistics & Probability Letters
    • Ehm, W.1
  • 9
    • 8344239069 scopus 로고    scopus 로고
    • On multivariate goodness of fit and two sample testing
    • J. H. Friedman. On multivariate goodness of fit and two sample testing. eConf, 2003.
    • (2003) eConf
    • Friedman, J.H.1
  • 10
    • 77951951390 scopus 로고    scopus 로고
    • Kernel choice and classifiability for rkhs embeddings of probability distributions
    • K. Fukumizu, A. Gretton, Gert R. L., B. Schölkopf, and B. Sriperumbudur. Kernel choice and classifiability for rkhs embeddings of probability distributions. NIPS, 2009.
    • (2009) NIPS
    • Fukumizu, K.1    Gretton, A.2    Gert, R.L.3    Schölkopf, B.4    Sriperumbudur, B.5
  • 12
    • 33750587254 scopus 로고    scopus 로고
    • Measuring statistical dependence with hilbert-schmidt norms
    • A. Gretton, O. Bousquet, A. Smola, and B. Schölkopf. Measuring statistical dependence with hilbert-schmidt norms. In ALT, 2005.
    • (2005) ALT
    • Gretton, A.1    Bousquet, O.2    Smola, A.3    Schölkopf, B.4
  • 16
    • 84857892556 scopus 로고    scopus 로고
    • Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics
    • M. U. Gutmann and A. Hyvärinen. Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics. JMLR, 2012.
    • (2012) JMLR
    • Gutmann, M.U.1    Hyvärinen, A.2
  • 17
    • 84958589374 scopus 로고    scopus 로고
    • Deep residual learning for image recognition
    • K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition. CVPR, 2015.
    • (2015) CVPR
    • He, K.1    Zhang, X.2    Ren, S.3    Sun, J.4
  • 19
    • 85018899841 scopus 로고    scopus 로고
    • Interpretable distribution features with maximum testing power
    • W. Jitkrittum, Z. Szabo, K. Chwialkowski, and A. Gretton. Interpretable Distribution Features with Maximum Testing Power. NIPS, 2016.
    • (2016) NIPS
    • Jitkrittum, W.1    Szabo, Z.2    Chwialkowski, K.3    Gretton, A.4
  • 20
    • 84990034290 scopus 로고    scopus 로고
    • Perceptual losses for real-time style transfer and super-resolution
    • J. Johnson, A. Alahi, and L. Fei-Fei. Perceptual Losses for Real-Time Style Transfer and Super-Resolution. ECCV, 2016.
    • (2016) ECCV
    • Johnson, J.1    Alahi, A.2    Fei-Fei, L.3
  • 22
    • 85083951076 scopus 로고    scopus 로고
    • A method for stochastic optimization
    • D. Kingma and J. Ba. Adam: A method for stochastic optimization. ICLR, 2015.
    • (2015) ICLR
    • Kingma, D.1    Adam, J.Ba.2
  • 23
    • 0001869771 scopus 로고
    • Sulla determinazione empirica di una legge di distribuzione
    • A. N. Kolmogorov. Sulla determinazione empirica di una legge di distribuzione. Inst. Ital. Attuari, 1933.
    • (1933) Inst. Ital. Attuari
    • Kolmogorov, A.N.1
  • 24
  • 27
    • 84965161496 scopus 로고    scopus 로고
    • Statistical model criticism using kernel two sample tests
    • J. R. Lloyd and Z. Ghahramani. Statistical model criticism using kernel two sample tests. NIPS, 2015.
    • (2015) NIPS
    • Lloyd, J.R.1    Ghahramani, Z.2
  • 28
    • 84965164729 scopus 로고    scopus 로고
    • Towards a learning theory of cause-effect inference
    • D. Lopez-Paz, K. Muandet, B. Schölkopf, and I. Tolstikhin. Towards a learning theory of cause-effect inference. In ICML, pp. 1452-1461, 2015.
    • (2015) ICML , pp. 1452-1461
    • Lopez-Paz, D.1    Muandet, K.2    Schölkopf, B.3    Tolstikhin, I.4
  • 29
    • 0002322469 scopus 로고
    • On a test of whether one of two random variables is stochastically larger than the other
    • H. B. Mann and D. R. Whitney. On a test of whether one of two random variables is stochastically larger than the other. The annals of mathematical statistics, 1947.
    • (1947) The Annals of Mathematical Statistics
    • Mann, H.B.1    Whitney, D.R.2
  • 30
    • 84997719736 scopus 로고    scopus 로고
    • Linking losses for density ratio and class-probability estimation
    • A. K. Menon and C. S. Ong. Linking losses for density ratio and class-probability estimation. ICML, 2016.
    • (2016) ICML
    • Menon, A.K.1    Ong, C.S.2
  • 31
    • 84898956512 scopus 로고    scopus 로고
    • Distributed representations of words and phrases and their compositionality
    • T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean. Distributed representations of words and phrases and their compositionality. NIPS, 2013.
    • (2013) NIPS
    • Mikolov, T.1    Sutskever, I.2    Chen, K.3    Corrado, G.S.4    Dean, J.5
  • 34
    • 84979916807 scopus 로고    scopus 로고
    • Distinguishing cause from effect using observational data: Methods and benchmarks
    • J. M. Mooij, J. Peters, D. Janzing, J. Zscheischler, and B. Schölkopf. Distinguishing cause from effect using observational data: methods and benchmarks. JMLR, 2016.
    • (2016) JMLR
    • Mooij, J.M.1    Peters, J.2    Janzing, D.3    Zscheischler, J.4    Schölkopf, B.5
  • 35
    • 85018914753 scopus 로고    scopus 로고
    • F-GaN: Training generative neural samplers using variational divergence minimization
    • S. Nowozin, B. Cseke, and R. Tomioka. f-GAN: Training generative neural samplers using variational divergence minimization. NIPS, 2016.
    • (2016) NIPS
    • Nowozin, S.1    Cseke, B.2    Tomioka, R.3
  • 38
    • 70349349170 scopus 로고    scopus 로고
    • Cambridge University Press
    • J. Pearl. Causality. Cambridge University Press, 2009.
    • (2009) Causality
    • Pearl, J.1
  • 39
    • 65549168742 scopus 로고    scopus 로고
    • Machine learning classifiers and fMRI: A tutorial overview
    • F. Pereira, T. Mitchell, and M. Botvinick. Machine learning classifiers and fMRI: a tutorial overview. Neuroimage, 2009.
    • (2009) Neuroimage
    • Pereira, F.1    Mitchell, T.2    Botvinick, M.3
  • 40
    • 84858766275 scopus 로고    scopus 로고
    • Estimation of information theoretic measures for continuous random variables
    • F. Pérez-Cruz. Estimation of information theoretic measures for continuous random variables. NIPS, 2009.
    • (2009) NIPS
    • Pérez-Cruz, F.1
  • 41
    • 85083950271 scopus 로고    scopus 로고
    • Unsupervised representation learning with deep convolutional generative adversarial networks
    • A. Radford, L. Metz, and S. Chintala. Unsupervised representation learning with deep convolutional generative adversarial networks. ICLR, 2016.
    • (2016) ICLR
    • Radford, A.1    Metz, L.2    Chintala, S.3
  • 44
    • 84965162267 scopus 로고    scopus 로고
    • On the high dimensional power of a linear-time two sample test under mean-shift alternatives
    • S. J. Reddi, A. Ramdas, B. Póczos, A. Singh, and L. A. Wasserman. On the high dimensional power of a linear-time two sample test under mean-shift alternatives. AISTATS, 2015.
    • (2015) AISTATS
    • Reddi, S.J.1    Ramdas, A.2    Póczos, B.3    Singh, A.4    Wasserman, L.A.5
  • 45
    • 79955815221 scopus 로고    scopus 로고
    • Information, divergence and risk for binary experiments
    • M. D. Reid and R. C. Williamson. Information, divergence and risk for binary experiments. JMLR, 2011.
    • (2011) JMLR
    • Reid, M.D.1    Williamson, R.C.2
  • 48
    • 0001893703 scopus 로고
    • On the estimation of the discrepancy between empirical curves of distribution for two independent samples
    • N. V. Smirnov. On the estimation of the discrepancy between empirical curves of distribution for two independent samples. Bull. Math. Univ. Moscou, 1939.
    • (1939) Bull. Math. Univ. Moscou
    • Smirnov, N.V.1
  • 50
    • 0345399126 scopus 로고
    • The probable error of a mean
    • Student
    • Student. The probable error of a mean. Biometrika, 1908.
    • (1908) Biometrika
  • 52
    • 85083950260 scopus 로고    scopus 로고
    • A note on the evaluation of generative models
    • L. Theis, A. van den Oord, and M. Bethge. A note on the evaluation of generative models. ICLR, 2016.
    • (2016) ICLR
    • Theis, L.1    Van Den Oord, A.2    Bethge, M.3
  • 54
    • 0001884644 scopus 로고
    • Individual comparisons by ranking methods
    • F. Wilcoxon. Individual comparisons by ranking methods. Biometrics bulletin, 1945.
    • (1945) Biometrics Bulletin
    • Wilcoxon, F.1
  • 55
    • 84960434044 scopus 로고    scopus 로고
    • Two-sample homogeneity tests based on divergence measures
    • M. Wornowizki and R. Fried. Two-sample homogeneity tests based on divergence measures. Computational Statistics, 2016.
    • (2016) Computational Statistics
    • Wornowizki, M.1    Fried, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.