2 citations · 5 across the 17 of their papers we have counts for
4 papers · 1 filter
A Review of Neuroscience-Inspired Machine Learning
Alexander Ororbia, Ankur Mali, Adam Kohan +2
One major criticism of deep learning centers around the biological implausibility of the credit assignment schema used for learning -- backpropagation of errors. This implausibilit…
The Neural State Pushdown Automata
Ankur Mali, Alexander Ororbia, C. Lee Giles
In order to learn complex grammars, recurrent neural networks (RNNs) require sufficient computational resources to ensure correct grammar recognition. A widely-used approach to exp…
Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations
Alexander Ororbia, Ankur Mali, C. Lee Giles +1
Temporal models based on recurrent neural networks have proven to be quite powerful in a wide variety of applications. However, training these models often relies on back-propagati…
Biologically Motivated Algorithms for Propagating Local Target Representations
Alexander G. Ororbia, Ankur Mali
Finding biologically plausible alternatives to back-propagation of errors is a fundamentally important challenge in artificial neural network research. In this paper, we propose a…