Building high-level features using large scale unsupervised learning

Details Building high-level features using large scale unsupervised learning Building high-level features using large scale unsupervised learning

2011-12-29

arxiv.org/abs/1112.6209v1

Computer Science

Learning

Scientific paper

We consider the problem of building detectors for high-level concepts using only unsupervised feature learning. For example, we would like to understand if it is possible to learn a face detector using only unlabeled images downloaded from the internet. To answer this question, we trained a simple feature learning algorithm on a large dataset of images (10 million images, each image is 200x200). The simulation is performed on a cluster of 1000 machines with fast network hardware for one week. Extensive experimental results reveal surprising evidence that such high-level concepts can indeed be learned using only unlabeled data and a simple learning algorithm.

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