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NIPS
2008
15 years 4 months ago
Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
We show how improved sequences for magnetic resonance imaging can be found through optimization of Bayesian design scores. Combining approximate Bayesian inference and natural ima...
Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann,...
NIPS
2007
15 years 4 months ago
Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data
Content-based image suggestion (CBIS) targets the recommendation of products based on user preferences on the visual content of images. In this paper, we motivate both feature sel...
Sabri Boutemedjet, Djemel Ziou, Nizar Bouguila
NIPS
2007
15 years 4 months ago
Bundle Methods for Machine Learning
We present a globally convergent method for regularized risk minimization problems. Our method applies to Support Vector estimation, regression, Gaussian Processes, and any other ...
Alex J. Smola, S. V. N. Vishwanathan, Quoc V. Le
NIPS
2007
15 years 4 months ago
Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms
The peristimulus time histogram (PSTH) and its more continuous cousin, the spike density function (SDF) are staples in the analytic toolkit of neurophysiologists. The former is us...
Dominik Endres, Mike W. Oram, Johannes E. Schindel...
NIPS
2007
15 years 4 months ago
Bayesian Co-Training
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumption...
Shipeng Yu, Balaji Krishnapuram, Rómer Rosa...