Fetching the paper…
Reading the bibliography…
In the modern age, rankings data is ubiquitous and it is useful for a variety of applications such as recommender systems, multi-object tracking and preference learning.
Theory of Reproducing Kernels
Aronszajn, N. 1950 · 1950
Earlier work this paper cites.
A new Monte Carlo techinique: antithetic variates
Hammersley, J. M., & Morton, K. W. 1956 · 1956
Earlier work this paper cites.
Pattern Classification And Scene Analysis
Duda, R. O., & Hart, P. E. 1973 · 1973
Earlier work this paper cites.
The Representation Theory of the Symmetric Groups
James, G. D. 1978 · 1978
Earlier work this paper cites.
Approximation Theorems of Mathematical Statistics
Serfling, R. J. 1980 · 1980
Earlier work this paper cites.
Harmonic analysis on semigroups
Berg, C., Christensen, J. P. R., & Ressel, P. 1984 · 1984
Earlier work this paper cites.
On Chebyshev’s other inequality
Fink, A. M., & Jodeit, M. 1984 · 1984
Earlier work this paper cites.
Group Representations in Probability and Statistics
Diaconis, P. 1988 · 1988
Earlier work this paper cites.
A training algorithm for optimal margin classifiers
Boser, B. E., Guyon, I. M., & Vapnik, V. N. 1992 · 1992
Earlier work this paper cites.
Support-vector networks
Cortes, C., & Vapnik, V. N. 1995 · 1995
Earlier work this paper cites.
The art of computer programming
Knuth, D. 1998 · 1998
Earlier work this paper cites.
Regression and Classification Using Gaussian Process Priors
M., Neal. R. 1998 · 1998
Earlier work this paper cites.
Convolution Kernels on Discrete Structures
Haussler, David. 1999 · 1999
Cited alongside, same era.
Kernel principal component analysis
Schölkopf, B., Smola, A. J., & Müller, K. R. 1999 · 1999
Cited alongside, same era.
Real Analysis and Probability
Dudley, R. 2002 · 2002
Cited alongside, same era.
Learning with kernels: support vector machines, regularisation, optimisation and beyond
Schölkopf, B., & Smola, A. 2002 · 2002
Cited alongside, same era.
Marginalised kernels for biological sequences
Tsuda, K., Kin, T., & Asai, K. 2002 · 2002
Cited alongside, same era.
Reproducing Hilbert Spaces for Probability and Statistics
Berlinet, A., & Thomas-Agnan, C. 2004 · 2004
Cited alongside, same era.
Characteristic kernels on groups and semigroups
Fukumizu, K., Sriperumbudur, B., Gretton, A., & Schölkopf, B. 2009 · 2009
Later among the works it cites.
Mining Complex Data
Kamishima, T., & Akaho, S. 2009 · 2009
Later among the works it cites.
Super-Samples from Kernel Herding
Chen, Y., Welling, M., & Smola, A. 2010 · 2010
Later among the works it cites.
Ranking with kernels in Fourier space
Kondor, R., & Barbosa, M. 2010 · 2010
Later among the works it cites.
Universality, characteristic Kernels and RKHS embedding of measures
Sriperumbudur, B. K., Fukumizu, K., & Lanckriet, G. R. G. 2011 · 2011
Later among the works it cites.
GPy: A Gaussian process framework in python
GPy. since 2012 · 2012
Later among the works it cites.
A Kernel two sample test
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Wendland, H. 2005 · 2004
Cited alongside, same era.
Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. 2006 · 2006
Cited alongside, same era.
Nonparametric quantile estimation
Takeuchi, I., Le, Q. V., Sears, T. D., & Smola, A. 2006 · 2006
Cited alongside, same era.
A test for the two-sample problem based on empirical characteristic functions
Alba Fernández, V., Jiménez Gamero, M. D., & Muñoz García, J. 2007 · 2007
Cited alongside, same era.
Multi-object tracking with representations of the symmetric group
Kondor, R., Howard, A., & Jebara, T. 2007 · 2007
Cited alongside, same era.
Encyclopedia of Distances
Deza, M. M., & Deza, E. 2009 · 2009
Cited alongside, same era.
Gretton, A., Borgwardt, K. M., Rasch, M. J., Schölkopf, B., & Smola, A. 2012 · 2012
Later among the works it cites.
Equivalence of distance-based and RKHS-based statistics in hypothesis testing
Sejdinovic, D., Sriperumbudur, B., Gretton, A., & Fukumizu, K. 2013 · 2013
Later among the works it cites.
The Kendall and Mallows Kernels for Permutations
Jiao, Y., & Vert, J. P. 2015 · 2015
Later among the works it cites.
Sampling and learning Mallows and Generalized Mallows models under the Cayley distance
Irurozki, E.and Calvo, B., & Lozano, J. A. 2016 · 2016
Later among the works it cites.
Universality of Mallows’ and degeneracy of Kendall’s kernels for rankings
Mania, H., Ramdas, A., Wainwright, M. J., Jordan, M. I., & Recht, B. 2016 · 2016
Later among the works it cites.