
Neuroscienceinspired online unsupervised learning algorithms
Although the currently popular deep learning networks achieve unpreceden...
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Blind nonnegative source separation using biological neural networks
Blind source separation, i.e. extraction of independent sources from a m...
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Why do similarity matching objectives lead to Hebbian/antiHebbian networks?
Modeling selforganization of neural networks for unsupervised learning ...
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Selfcalibrating Neural Networks for Dimensionality Reduction
Recently, a novel family of biologically plausible online algorithms for...
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Optimization theory of Hebbian/antiHebbian networks for PCA and whitening
In analyzing information streamed by sensory organs, our brains face cha...
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A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks
To make sense of the world our brains must analyze highdimensional data...
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A Hebbian/AntiHebbian Network for Online Sparse Dictionary Learning Derived from Symmetric Matrix Factorization
Olshausen and Field (OF) proposed that neural computations in the primar...
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A Hebbian/AntiHebbian Network Derived from Online NonNegative Matrix Factorization Can Cluster and Discover Sparse Features
Despite our extensive knowledge of biophysical properties of neurons, th...
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A Hebbian/AntiHebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data
Neural network models of early sensory processing typically reduce the d...
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A Neuron as a Signal Processing Device
A neuron is a basic physiological and computational unit of the brain. W...
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Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics
Artificial neural networks that learn to perform Principal Component Ana...
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Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching
Big data problems frequently require processing datasets in a streaming ...
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A Spiking Neural Network with Local Learning Rules Derived From Nonnegative Similarity Matching
The design and analysis of spiking neural network algorithms will be acc...
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Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks
Synaptic plasticity is widely accepted to be the mechanism behind learni...
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A Closer Look at Disentangling in βVAE
In many data analysis tasks, it is beneficial to learn representations w...
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Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
A fundamental question in modern machine learning is how deep neural net...
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Supervised Deep Similarity Matching
We propose a novel biologicallyplausible solution to the credit assignm...
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Blind Bounded Source Separation Using Neural Networks with Local Learning Rules
An important problem encountered by both natural and engineered signal p...
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Cengiz Pehlevan
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