References in zbMATH (referenced in 19 articles )

Showing results 1 to 19 of 19.
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  1. Mooij, Joris M.; Peters, Jonas; Janzing, Dominik; Zscheischler, Jakob; Schölkopf, Bernhard: Distinguishing cause from effect using observational data: methods and benchmarks (2016)
  2. Merola, Giovanni Maria: Least squares sparse principal component analysis: a backward elimination approach to attain large loadings (2015)
  3. Chen, Yu-Chuan; Ha, Hyejung; Kim, Hyunjoong; Ahn, Hongshik: Canonical forest (2014)
  4. Reif, Matthias; Shafait, Faisal: Efficient feature size reduction via predictive forward selection (2014) ioport
  5. Reif, Matthias; Shafait, Faisal; Goldstein, Markus; Breuel, Thomas; Dengel, Andreas: Automatic classifier selection for non-experts (2014) ioport
  6. Gascón-Moreno, J.; Ortiz-García, E.G.; Salcedo-Sanz, S.; Carro-Calvo, L.; Saavedra-Moreno, B.; Portilla-Figueras, A.: Evolutionary optimization of multi-parametric kernel $\epsilon$-SVMr for forecasting problems (2013) ioport
  7. Gu, Chong; Jeon, Yongho; Lin, Yi: Nonparametric density estimation in high-dimensions (2013)
  8. Zhang, Li; Zhou, WeiDa: 1-norm support vector novelty detection and its sparseness (2013)
  9. Mendes-Moreira, João; Soares, Carlos; Jorge, Alípio Mário; Sousa, Jorge Freire De: Ensemble approaches for regression: a survey (2012)
  10. Ñanculef, Ricardo; Valle, Carlos; Allende, Héctor; Moraga, Claudio: Training regression ensembles by sequential target correction and resampling (2012)
  11. Reif, Matthias; Shafait, Faisal; Dengel, Andreas: Meta-learning for evolutionary parameter optimization of classifiers (2012) ioport
  12. Frey, Jesse; Ozturk, Omer: Constrained estimation using judgment post-stratification (2011)
  13. Kim, Hyunjoong; Kim, Hyeuk; Moon, Hojin; Ahn, Hongshik: A weight-adjusted voting algorithm for ensembles of classifiers (2011)
  14. Scherbart, Alexandra; Nattkemper, Tim W.: Looking inside self-organizing map ensembles with resampling and negative correlation learning (2011)
  15. Yu, Yanfang; Qian, Feng; Liu, Huimin: Quantum clustering-based weighted linear programming support vector regression for multivariable nonlinear problem (2010) ioport
  16. Mierswa, Ingo; Morik, Katharina: About the non-convex optimization problem induced by non-positive semidefinite kernel learning (2008)
  17. Rentería, Paúl; Milidiú, Ruy; Souza, Rafael: MKPLS approach: switching strategies for the non-linear multi-kernel PLSR (2007)
  18. Milidiú, Ruy L.; Rentería, Raúl P.: DPLS and PPLS: Two PLS algorithms for large data sets (2005)
  19. Nascimento, Susana: Fuzzy clustering via proportional membership model. (2005)