Add to ORKGSchulz A, Gisbrecht A, Hammer B. Relevance learning for dimensionality reduction. In: Verleysen M, ed. ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium: i6doc.com; 2014: 165-170
Nowadays, the advanced technologies make amounts of data growing in a fast paced way. In many applic...
Machine learning methods are used to build models for classification and regression tasks, among oth...
Kaestner M, Hammer B, Biehl M, Villmann T. Generalized Functional Relevance Learning Vector Quantiza...
Abstract. Nonlinear dimensionality reduction (NLDR) techniques offer powerful data visualization sch...
Schleif F-M, Gisbrecht A, Hammer B. Relevance learning for short high-dimensional time series in the...
Schulz A, Hammer B. Metric Learning in Dimensionality Reduction. In: Proceedings of the Internation...
Bojer T, Hammer B, Schunk D, Tluk von Toschanowitz K. Relevance determination in learning vector qua...
Schneider P, Bunte K, Stiekema H, Hammer B, Villmann T, Biehl M. Regularization in Matrix Relevance ...
Pfannschmidt L. Relevance learning for redundant features. Bielefeld: Universität Bielefeld; 2021.Fe...
Gisbrecht A, Hammer B. Relevance learning in generative topographic mapping. Neurocomputing. 2011;74...
Tluk von Toschanowitz K, Hammer B, Ritter H. Relevance determination in reinforcement learning. In: ...
Bunte K, Biehl M, Hammer B. Supervised dimension reduction mappings. In: Verleysen M, ed. European S...
Kaestner M, Hammer B, Biehl M, Villmann T. Functional relevance learning in generalized learning vec...
Bunte K, Biehl M, Hammer B. Dimensionality Reduction Mappings. In: IEEE Computational Intelligence S...
Hammer B, Gisbrecht A, Schulz A. Applications of discriminative dimensionality reduction. In: Proce...
Nowadays, the advanced technologies make amounts of data growing in a fast paced way. In many applic...
Machine learning methods are used to build models for classification and regression tasks, among oth...
Kaestner M, Hammer B, Biehl M, Villmann T. Generalized Functional Relevance Learning Vector Quantiza...
Abstract. Nonlinear dimensionality reduction (NLDR) techniques offer powerful data visualization sch...
Schleif F-M, Gisbrecht A, Hammer B. Relevance learning for short high-dimensional time series in the...
Schulz A, Hammer B. Metric Learning in Dimensionality Reduction. In: Proceedings of the Internation...
Bojer T, Hammer B, Schunk D, Tluk von Toschanowitz K. Relevance determination in learning vector qua...
Schneider P, Bunte K, Stiekema H, Hammer B, Villmann T, Biehl M. Regularization in Matrix Relevance ...
Pfannschmidt L. Relevance learning for redundant features. Bielefeld: Universität Bielefeld; 2021.Fe...
Gisbrecht A, Hammer B. Relevance learning in generative topographic mapping. Neurocomputing. 2011;74...
Tluk von Toschanowitz K, Hammer B, Ritter H. Relevance determination in reinforcement learning. In: ...
Bunte K, Biehl M, Hammer B. Supervised dimension reduction mappings. In: Verleysen M, ed. European S...
Kaestner M, Hammer B, Biehl M, Villmann T. Functional relevance learning in generalized learning vec...
Bunte K, Biehl M, Hammer B. Dimensionality Reduction Mappings. In: IEEE Computational Intelligence S...
Hammer B, Gisbrecht A, Schulz A. Applications of discriminative dimensionality reduction. In: Proce...
Nowadays, the advanced technologies make amounts of data growing in a fast paced way. In many applic...
Machine learning methods are used to build models for classification and regression tasks, among oth...
Kaestner M, Hammer B, Biehl M, Villmann T. Generalized Functional Relevance Learning Vector Quantiza...