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Neurocomputing, Volume 80
Volume 80, March 2012
- Jaakko Peltonen, Tapani Raiko, Samuel Kaski:
Machine learning for signal processing 2010. 1-2 - Paolo Piro, Richard Nock, Frank Nielsen, Michel Barlaud:
Leveraging k-NN for generic classification boosting. 3-9 - Ricardo Henao, Ole Winther:
Predictive active set selection methods for Gaussian processes. 10-18 - Genaro Daza-Santacoloma, Germán Castellanos-Domínguez, José C. Príncipe:
Locally linear embedding based on correntropy measure for visualization and classification. 19-30 - Lev Faivishevsky, Jacob Goldberger:
Dimensionality reduction based on non-parametric mutual information. 31-37 - Robert Peharz, Franz Pernkopf:
Sparse nonnegative matrix factorization with ℓ0-constraints. 38-46 - Ryan D. Turner, Carl Edward Rasmussen:
Model based learning of sigma points in unscented Kalman filtering. 47-53 - Morten Mørup, Lars Kai Hansen:
Archetypal analysis for machine learning and data mining. 54-63 - Paris Smaragdis, Bhiksha Raj:
The Markov selection model for concurrent speech recognition. 64-72 - Adrien Combaz, Nikolay Chumerin, Nikolay V. Manyakov, Arne Robben, Johan A. K. Suykens, Marc M. Van Hulle:
Towards the detection of error-related potentials and its integration in the context of a P300 speller brain-computer interface. 73-82 - Khondaker Abdullah Al Mamun, Michael Mace, Lalit Gupta, Carl A. Verschuur, Mark E. Lutman, Maria Stokes, Ravi Vaidyanathan, Shouyan Wang:
Robust real-time identification of tongue movement commands from interferences. 83-92 - Hirotaka Hachiya, Masashi Sugiyama, Naonori Ueda:
Importance-weighted least-squares probabilistic classifier for covariate shift adaptation with application to human activity recognition. 93-101 - Jan Oksanen, Jarmo Lundén, Visa Koivunen:
Reinforcement learning based sensing policy optimization for energy efficient cognitive radio networks. 102-110 - Ata Kabán, Sakinah Ali Pitchay:
Single-frame image recovery using a Pearson type VII MRF. 111-118 - Miguel A. Prada, Janne Toivola, Jyrki Kullaa, Jaakko Hollmén:
Three-way analysis of structural health monitoring data. 119-128
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