Multiple--Instance Learning: Christoffel Function Approach to Distribution Regression Problem

Paul G Nevai, “Géza Freud, Orthogonal Polynomials. Christoffel Functions. A Case Study,” Journal Of Approximation Theory 48

1986

Earlier work this paper cites.

Bernhard Beckermann, On the numerical condition of polynomial bases: estimates for the condition number of Vandermonde, Krylov and Hankel matrices , Ph.D. thesis , Habilitationsschrift, Universität Hannover (1996)

1996

Earlier work this paper cites.

Jun Yang, Review of multi-instance learning and its applications , Tech. Rep. (Tech. Rep, 2005)

2005

Earlier work this paper cites.

Vilmos Totik, “Orthogonal polynomials,” Surveys in Approximation Theory 1

2005

Cited alongside, same era.

Zoltán Szabó, Arthur Gretton, Barnabás Póczos, and Bharath Sriperumbudur, “Learning theory for distribution regression,” arXiv preprint arXiv:1411.2066 (2014)

Original

2014

Cited alongside, same era.

Vladislav Gennadievich Malyshkin, (2014), the code for polynomials calculation, http://www.ioffe.ru/LNEPS/malyshkin/code.html

2014

Cited alongside, same era.

Vladislav Gennadievich Malyshkin, “Radon–Nikodym approximation in application to image analysis. http://arxiv.org/abs/1511.01887 ,” ArXiv e-prints (2015) , arXiv:1511.01887 [cs.CV]

Original

2015

Closest in time.

Vladislav Gennadievich Malyshkin and Ray Bakhramov, “Mathematical Foundations of Realtime Equity Trading. Liquidity Deficit and Market Dynamics. Automated Trading Machines. http://arxiv.org/abs/1510.05510 ,” ArXiv e-prints (2015) , arXiv:1510.05510 [q-fin.CP]

Original

2015

Closest in time.