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Ray T. Chen

2 accepted papers

2021

Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization

AAAI 2021technical

Optical neural networks (ONNs) have demonstrated record-breaking potential in high-performance neuromorphic computing due to their ultra-high execution speed and low energy consumption. However, current learning protocols fail to provide scalable and efficient solutions to photonic circuit optimizat…

Cited by 33SourcePDFScholar
2021

Towards Memory-Efficient Neural Networks via Multi-Level In Situ Generation

ICCV 2021poster

Deep neural networks (DNN) have shown superior performance in a variety of tasks. As they rapidly evolve, their escalating computation and memory demands make it challenging to deploy them on resource-constrained edge devices. Though extensive efficient accelerator designs, from traditional electron…

Cited by 5PDFcodeScholar