Locality sensitive hash is well known technique for approximate nearest search and dimensions reduction. Combining it with dnn may reduce the complexity of the

Locality sensitive hash is well known technique for approximate nearest search and dimensions reduction. Combining it with dnn may reduce the complexity of the dataset. But I don't know if in this setting the parameters of the lsh are learnable via backprop?