Compressive Clustering with an Optical Processing Unit
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 21 references that are in the map. First posted on arXiv 13 Jun 2022.
Builds on
6 of 21 references.
References · 6
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
- 2015Random Projections through multiple optical scattering: Approximating kernels at the speed of lightcited by 16
- 2016Sketching for Large-Scale Learning of Mixture Modelscited by 14
- 2021Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learningcited by 13
- 2019Kernel computations from large-scale random features obtained by Optical Processing Unitscited by 6
- 2019Fast Optical System Identification by Numerical Interferometrycited by 4
Built on by
Citing papers per year: 2023: 1.
1 paper.