jens
7b34529b24
git-svn-id: http://moon:8086/svn/matlab/trunk@91 801c6759-fa7c-4059-a304-17956f83a07c
23 lines
816 B
Matlab
23 lines
816 B
Matlab
function [ stack ] = initialize_weights( ei )
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%INITIALIZE_WEIGHTS Random weight structures for a network architecture
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% eI describes a network via the fields layerSizes, inputDim, and outputDim
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%
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% This uses Xavier's weight initialization tricks for better backprop
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% See: X. Glorot, Y. Bengio. Understanding the difficulty of training
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% deep feedforward neural networks. AISTATS 2010.
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%% initialize hidden layers
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stack = cell(1, numel(ei.layer_sizes));
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for l = 1 : numel(ei.layer_sizes)
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if l > 1
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prev_size = ei.layer_sizes(l-1);
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else
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prev_size = ei.input_dim;
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end;
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cur_size = ei.layer_sizes(l);
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% Xaxier's scaling factor
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s = sqrt(6) / sqrt(prev_size + cur_size);
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stack{l}.W = rand(cur_size, prev_size)*2*s - s;
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stack{l}.b = zeros(cur_size, 1);
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end
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