Implement unshared convolution / Locally-Connected Layer
A locally-connected layer is similar to convolution but instead of reusing the same convolution filter across the image patches it stacks new ones after moving by each stride.

Implementations:

- [pylearn2](https://github.com/lisa-lab/pylearn2/tree/master/pylearn2/packaged_dependencies/theano_linear/unshared_conv)
- [Keras with Tensorflow backend](https://github.com/keras-team/keras/blob/ebdc1c8759f65768212b7e7113b5cae82e9df3d4/keras/backend/tensorflow_backend.py#L4335)
- Theano: https://github.com/Theano/Theano/issues/5620
- Torch: https://github.com/torch/nn/blob/master/SpatialConvolutionLocal.lua

Keras implementation is slow and so is Torch's (C + Lua) https://groups.google.com/forum/#!topic/torch7/KCRNkKcYzfs

NN Arch using it:
  - [Facebook DeepFace (CVPR 14')](http://www.cs.toronto.edu/~ranzato/publications/taigman_cvpr14.pdf)