Compressive Clustering with an Optical Processing Unit
arXiv:2206.05928v21 citationsh-index: 59
AI Analysis
This work addresses computational efficiency in clustering for researchers, but it is incremental as it adapts existing methods to new hardware.
The authors tackled the problem of adapting compressive clustering to use Optical Processing Units for computing random Fourier features, and they proposed tools for tuning a critical hyper-parameter in this pipeline.
We explore the use of Optical Processing Units (OPU) to compute random Fourier features for sketching, and adapt the overall compressive clustering pipeline to this setting. We also propose some tools to help tuning a critical hyper-parameter of compressive clustering.