Global ETD Search
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Showing 1 to 4 of 4 for “"Neural Network Quantization"”.
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LightMARL : smart swarm coordination in urban spaces
… To improve computation, the framework utilizes neural network quantization, structured pruning, and knowledge distillation tailored for multi-agent policy optimization (MAPPO). These methods decrease model size and computational demands while maintaining essential coordination behaviors. To …
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TwinDNN: A tale of two deep neural networks
Compression technologies for deep neural networks (DNNs), such as weight quantization, have been widely investigated to reduce the model size so that they can be implemented on hardware with strict resource restrictions. However, one major disadvantage of model compression is accuracy degradation. …
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Adaptive model inference under computational resource constraints
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-05-01
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Accelerating Quantized DNNs with Dedicated Hardware Accelerators and RISC-V Processors Using Precision-Scalable Multipliers
L'abstract è presente nell'allegato / the abstract is in the attachment