• Publications
  • Influence
On the origin of the extracellular action potential waveform: A modeling study.
TLDR
A model system that captures features of experimentally recorded simultaneous intracellular and extracellular recordings of CA1 pyramidal neurons and demonstrates that the varied composition of ionic currents in different cells is reflected in the features of the EAP. Expand
Using extracellular action potential recordings to constrain compartmental models
TLDR
It is concluded that EAP recordings are an excellent source of data for the purpose of constraining compartmental models and the distinguishing characteristics of the waveform resulting from the distribution of active conductances are fairly invariant to changes of electrode position and detailed cellular morphology. Expand
Model selection for support vector machine classification
TLDR
The results for the evidence gradient ascent method show that also the exact evidence exhibits local optima, but these give test errors which are much less variable and also consistently lower than for the simpler model selection criteria. Expand
Visual attention and target detection in cluttered natural scenes
TLDR
It seems that this model, which had originally been designed not to find small, hidden military vehicles, but rather to find the few most obviously conspicuous objects in an image, performed as an efficient target detector on the Search–2 dataset. Expand
Biophysics of Extracellular Action Potentials
TLDR
It is concluded that matching EAP recordings are an excellent means of constraining compartmental models and underconstrains the parameters. Expand
High-amplitude positive spikes recorded extracellularly in cat visual cortex.
TLDR
There is a significant gap in the present understanding of either the spike-generation process in pyramidal neurons, the biophysics of extracellular recording, or both. Expand
Bayesian approach to feature selection and parameter tuning for support vector machine classifiers
TLDR
The final tuned hyperparameter values provide a useful criterion for pruning irrelevant features, and the measure of relevance with which to determine systematically how many features should be removed can improve classification accuracy in non-ARD SVMs. Expand
Fast Bayesian support vector machine parameter tuning with the Nystrom method
  • C. Gold, Peter Sollich
  • Mathematics
  • Proceedings. IEEE International Joint Conference…
  • 27 December 2005
We experiment with speeding up a Bayesian method for tuning the hyperparameters of a support vector machine (SVM) classifier. The Bayesian approach gives the gradients of the evidence as averagesExpand