Schneider P, Bunte K, Stiekema H, Hammer B, Villmann T, Biehl M. Regularization in Matrix Relevance Learning. IEEE Transactions on Neural Networks. 2010;21(5):831-840
Regularization techniques are widely employed in optimization-based approaches for solving ill-posed...
Bojer T, Hammer B, Schunk D, Tluk von Toschanowitz K. Relevance determination in learning vector qua...
The extension of Learning Vector Quantization by Matrix Relevance Learning is presented and discusse...
A In this paper, we present a regularization technique to extend recently proposed matrix learning s...
Schneider P, Biehl M, Hammer B. Adaptive relevance matrices in learning vector quantization. Neural ...
We present a regularization method which extends the recently introduced Generalized Matrix LVQ. Thi...
Schneider P, Biehl M, Hammer B. Relevance matrices in LVQ. In: Verleysen M, ed. Proc. Of European Sy...
Biehl M, Hammer B, Schleif F-M, Schneider P, Villmann T. Stationarity of Matrix Relevance Learning V...
Schulz A, Gisbrecht A, Hammer B. Relevance learning for dimensionality reduction. In: Verleysen M, e...
We propose a new matrix learning scheme to extend relevance learning vector quantization (RLVQ), an ...
Abstract. We propose in this contribution a method for l1-regularization in prototype based relevanc...
Biehl M, Hammer B, Schleif F-M, Schneider P, Villmann T. Stationarity of Matrix Relevance LVQ. In: ...
Hammer B, Villmann T. Generalized Relevance Learning Vector Quantization. Neural Networks. 2002;15(8...
In this contribution we propose a new regularization method for the Generalized Matrix Learning Vect...
We propose a new matrix learning scheme to extend Generalized Relevance Learning Vector Quantization...
Regularization techniques are widely employed in optimization-based approaches for solving ill-posed...
Bojer T, Hammer B, Schunk D, Tluk von Toschanowitz K. Relevance determination in learning vector qua...
The extension of Learning Vector Quantization by Matrix Relevance Learning is presented and discusse...
A In this paper, we present a regularization technique to extend recently proposed matrix learning s...
Schneider P, Biehl M, Hammer B. Adaptive relevance matrices in learning vector quantization. Neural ...
We present a regularization method which extends the recently introduced Generalized Matrix LVQ. Thi...
Schneider P, Biehl M, Hammer B. Relevance matrices in LVQ. In: Verleysen M, ed. Proc. Of European Sy...
Biehl M, Hammer B, Schleif F-M, Schneider P, Villmann T. Stationarity of Matrix Relevance Learning V...
Schulz A, Gisbrecht A, Hammer B. Relevance learning for dimensionality reduction. In: Verleysen M, e...
We propose a new matrix learning scheme to extend relevance learning vector quantization (RLVQ), an ...
Abstract. We propose in this contribution a method for l1-regularization in prototype based relevanc...
Biehl M, Hammer B, Schleif F-M, Schneider P, Villmann T. Stationarity of Matrix Relevance LVQ. In: ...
Hammer B, Villmann T. Generalized Relevance Learning Vector Quantization. Neural Networks. 2002;15(8...
In this contribution we propose a new regularization method for the Generalized Matrix Learning Vect...
We propose a new matrix learning scheme to extend Generalized Relevance Learning Vector Quantization...
Regularization techniques are widely employed in optimization-based approaches for solving ill-posed...
Bojer T, Hammer B, Schunk D, Tluk von Toschanowitz K. Relevance determination in learning vector qua...
The extension of Learning Vector Quantization by Matrix Relevance Learning is presented and discusse...
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