87 citations · 342 across the 15 of their papers we have counts for
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Optimization theory of Hebbian/anti-Hebbian networks for PCA and whitening
Cengiz Pehlevan, Dmitri B. Chklovskii
In analyzing information streamed by sensory organs, our brains face challenges similar to those solved in statistical signal processing. This suggests that biologically plausible…
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks
Cengiz Pehlevan, Dmitri B. Chklovskii
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, modelling e…
A Hebbian/Anti-Hebbian Network Derived from Online Non-Negative Matrix Factorization Can Cluster and Discover Sparse Features
Cengiz Pehlevan, Dmitri B. Chklovskii
Despite our extensive knowledge of biophysical properties of neurons, there is no commonly accepted algorithmic theory of neuronal function. Here we explore the hypothesis that sin…
A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data
Cengiz Pehlevan, Tao Hu, Dmitri B. Chklovskii
Neural network models of early sensory processing typically reduce the dimensionality of streaming input data. Such networks learn the principal subspace, in the sense of principal…
A Hebbian/Anti-Hebbian Network for Online Sparse Dictionary Learning Derived from Symmetric Matrix Factorization
Tao Hu, Cengiz Pehlevan, Dmitri B. Chklovskii
Olshausen and Field (OF) proposed that neural computations in the primary visual cortex (V1) can be partially modeled by sparse dictionary learning. By minimizing the regularized r…