A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks

@inproceedings{Pehlevan2015ANT,
  title={A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks},
  author={Cengiz Pehlevan and Dmitri B. Chklovskii},
  booktitle={NIPS},
  year={2015}
}
To make sense of the world our brains must analyze high-dimensional datasets streamed by our sensory organs. Because such analysis begins with dimensionality reduction, modeling early sensory processing requires biologically plausible online dimensionality reduction algorithms. Recently, we derived such an algorithm, termed similarity matching, from a Multidimensional Scaling (MDS) objective function. However, in the existing algorithm, the number of output dimensions is set a priori by the… CONTINUE READING
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