You will be given a definition of a task first, then some input of the task.
In this task, you are given the abstract of a research paper. Your task is to generate a summary of this abstract. Your summary should not be very short, but it's better if it's not more than 30 words.

We recently observed that convolutional filters initialized
farthest apart from each other using offthe-
shelf pre-computed Grassmannian subspace
packing codebooks performed surprisingly well
across many datasets. Through this short paper,
we'd like to disseminate some initial results in this
regard in the hope that we stimulate the curiosity
of the deep-learning community towards considering
classical Grassmannian subspace packing
results as a source of new ideas for more efficient
initialization strategies.
Output:
Initialize weights using off-the-shelf Grassmannian codebooks, get faster training and better accuracy