Add to ORKGBunte K, Biehl M, Hammer B. Supervised dimension reduction mappings. In: Verleysen M, ed. European Symposium on Artificial Neural Networks. D side; 2011: pp. 281-286
There is a great interest in dimensionality reduction techniques for tackling the problem of high-di...
We introduce and study the learning scenario of supervised dimensionality reduction, which couples d...
Abstract- Classification is undoubtedly gaining major importance in the fields of machine learning, ...
Bunte K, Biehl M, Hammer B. Dimensionality Reduction Mappings. In: IEEE Computational Intelligence S...
Gisbrecht A, Hofmann D, Hammer B. Discriminative Dimensionality Reduction Mappings. In: Hollmén J, K...
The problem of dimension reduction is introduced as a way to overcome the curse of the dimensionalit...
Schulz A, Hammer B. Metric Learning in Dimensionality Reduction. In: Proceedings of the Internation...
When data objects that are the subject of analysis using machine learning techniques are described b...
We consider supervised dimension reduction (SDR) for problems with discrete inputs. Existing methods...
Dimension reduction can be seen as the transformation from a high order dimension to a low order dim...
Bunte K, Hammer B, Biehl M. Nonlinear dimension reduction and visualization of labeled data. In: Jia...
Bunte K, Biehl M, Hammer B. A General Framework for Dimensionality-Reducing Data Visualization Mappi...
Dimensionality reduction (DR) is often used as a preprocessing step in classification, but usually o...
Schulz A, Gisbrecht A, Hammer B. Relevance learning for dimensionality reduction. In: Verleysen M, e...
Hammer B, Gisbrecht A, Schulz A. Applications of discriminative dimensionality reduction. In: Proce...
There is a great interest in dimensionality reduction techniques for tackling the problem of high-di...
We introduce and study the learning scenario of supervised dimensionality reduction, which couples d...
Abstract- Classification is undoubtedly gaining major importance in the fields of machine learning, ...
Bunte K, Biehl M, Hammer B. Dimensionality Reduction Mappings. In: IEEE Computational Intelligence S...
Gisbrecht A, Hofmann D, Hammer B. Discriminative Dimensionality Reduction Mappings. In: Hollmén J, K...
The problem of dimension reduction is introduced as a way to overcome the curse of the dimensionalit...
Schulz A, Hammer B. Metric Learning in Dimensionality Reduction. In: Proceedings of the Internation...
When data objects that are the subject of analysis using machine learning techniques are described b...
We consider supervised dimension reduction (SDR) for problems with discrete inputs. Existing methods...
Dimension reduction can be seen as the transformation from a high order dimension to a low order dim...
Bunte K, Hammer B, Biehl M. Nonlinear dimension reduction and visualization of labeled data. In: Jia...
Bunte K, Biehl M, Hammer B. A General Framework for Dimensionality-Reducing Data Visualization Mappi...
Dimensionality reduction (DR) is often used as a preprocessing step in classification, but usually o...
Schulz A, Gisbrecht A, Hammer B. Relevance learning for dimensionality reduction. In: Verleysen M, e...
Hammer B, Gisbrecht A, Schulz A. Applications of discriminative dimensionality reduction. In: Proce...
There is a great interest in dimensionality reduction techniques for tackling the problem of high-di...
We introduce and study the learning scenario of supervised dimensionality reduction, which couples d...
Abstract- Classification is undoubtedly gaining major importance in the fields of machine learning, ...