Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons Lars Buesing, Wolfgang Maass Institute for Theoretical Computer Science

First Page		Document Content
Date: 2014-10-13 19:51:13 Computational neuroscience Neuroscience Nervous system Artificial neural networks Statistics Multivariate statistics Biophysics Biological neuron model Principal component analysis Artificial neuron Spike-timing-dependent plasticity Hebbian theory		Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons Lars Buesing, Wolfgang Maass Institute for Theoretical Computer Science Add to Reading List Source URL: www.gatsby.ucl.ac.uk Download Document from Source Website File Size: 385,45 KB Share Document on Facebook

	15 Mathematical Tools for Multivariate Character Analysis This chapter introduces a variety of tools from matrix algebra and multivariate statistics useful in the analysis of selection on multiple characters. Our primary DocID: 1u8YK - View Document
	Software package for Multivariate Analysis and Multivariate Time Series Analysis Version 2.0+ Brodgar was developed by: Highland Statistics Ltd. DocID: 1tX3L - View Document
	Semidefinite Optimization with Applications in Sparse Multivariate Statistics Alexandre d’Aspremont ORFE, Princeton University Joint work with L. El Ghaoui, M. Jordan, V. Krishnamurthy, G. Lanckriet, DocID: 1tFCF - View Document
	R: statistics for all of us R: an international statistical collaboratory Prepared for part of the symposium on Multivariate Statistical Methods in Individual Differences Research International Society for the Study of I DocID: 1tmk6 - View Document