38 citations · 86 across the 5 of their papers we have counts for
5 papers
Bringing Anatomical Information into Neuronal Network Models
Sacha Jennifer van Albada, Aitor Morales-Gregorio, Timo Dickscheid +6
For constructing neuronal network models computational neuroscientists have access to wide-ranging anatomical data that nevertheless tend to cover only a fraction of the parameters…
Efficient Dictionary Learning with Sparseness-Enforcing Projections
Markus Thom, Matthias Rapp, Günther Palm
Learning dictionaries suitable for sparse coding instead of using engineered bases has proven effective in a variety of image processing tasks. This paper studies the optimization…
Sparse Activity and Sparse Connectivity in Supervised Learning
Markus Thom, Günther Palm
Sparseness is a useful regularizer for learning in a wide range of applications, in particular in neural networks. This paper proposes a model targeted at classification tasks, whe…
Constant Time EXPected Similarity Estimation using Stochastic Optimization
Markus Schneider, Wolfgang Ertel, Günther Palm
A new algorithm named EXPected Similarity Estimation (EXPoSE) was recently proposed to solve the problem of large-scale anomaly detection. It is a non-parametric and distribution f…
Efficient Sparseness-Enforcing Projections
Markus Thom, Günther Palm
We propose a linear time and constant space algorithm for computing Euclidean projections onto sets on which a normalized sparseness measure attains a constant value. These non-con…