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» VLSI Implementation of Neural Networks
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ICML
2005
IEEE
14 years 8 months ago
Learning to rank using gradient descent
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
IJCNN
2008
IEEE
14 years 2 months ago
Large developing axonal arbors using a distributed and locally-reprogrammable address-event receiver
Abstract— We have designed a distributed and locally reprogrammable address event receiver. Incoming address-events are monitored simultaneously by all synapses, allowing for arb...
Simeon A. Bamford, Alan F. Murray, David J. Willsh...
IWANN
2007
Springer
14 years 1 months ago
Speeding Up the Dissimilarity Self-Organizing Maps by Branch and Bound
Abstract. This paper proposes to apply the branch and bound principle from combinatorial optimization to the Dissimilarity Self-Organizing Map (DSOM), a variant of the SOM that can...
Brieuc Conan-Guez, Fabrice Rossi
ICANN
2005
Springer
14 years 1 months ago
Smooth Bayesian Kernel Machines
Abstract. In this paper, we consider the possibility of obtaining a kernel machine that is sparse in feature space and smooth in output space. Smooth in output space implies that t...
Rutger W. ter Borg, Léon J. M. Rothkrantz
ICANN
2005
Springer
14 years 1 months ago
High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data
Multidimensional Scaling (MDS) is a powerful dimension reduction technique for embedding high-dimensional data into a lowdimensional target space. Thereby, the distance relationshi...
Marc Strickert, Stefan Teichmann, Nese Sreenivasul...