31 citations · 48 across the 5 of their papers we have counts for
7 papers
Spiking Neural Networks Through the Lens of Streaming Algorithms
Yael Hitron, Cameron Musco, Merav Parter
We initiate the study of biological neural networks from the perspective of streaming algorithms. Like computers, human brains suffer from memory limitations which pose a significa…
Winner-Take-All Computation in Spiking Neural Networks
Nancy Lynch, Cameron Musco, Merav Parter
In this work we study biological neural networks from an algorithmic perspective, focusing on understanding tradeoffs between computation time and network complexity. Our goal is t…
A Basic Compositional Model for Spiking Neural Networks
Nancy Lynch, Cameron Musco
We present a formal, mathematical foundation for modeling and reasoning about the behavior of , , which have been wi…
Neuro-RAM Unit with Applications to Similarity Testing and Compression in Spiking Neural Networks
Nancy Lynch, Cameron Musco, Merav Parter
We study distributed algorithms implemented in a simplified biologically inspired model for stochastic spiking neural networks. We focus on tradeoffs between computation time and n…
Computational Tradeoffs in Biological Neural Networks: Self-Stabilizing Winner-Take-All Networks
Nancy Lynch, Cameron Musco, Merav Parter
We initiate a line of investigation into biological neural networks from an algorithmic perspective. We develop a simplified but biologically plausible model for distributed comput…
Ant-Inspired Density Estimation via Random Walks
Cameron Musco, Hsin-Hao Su, Nancy Lynch
Many ant species employ distributed population density estimation in applications ranging from quorum sensing [Pra05], to task allocation [Gor99], to appraisal of enemy colony stre…
Distributed House-Hunting in Ant Colonies
Mohsen Ghaffari, Cameron Musco, Tsvetomira Radeva +1
We introduce the study of the ant colony house-hunting problem from a distributed computing perspective. When an ant colony's nest becomes unsuitable due to size constraints or dam…