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Adaptive Loss-Aware Quantization for Multi-Bit Networks
(2020)2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)We investigate the compression of deep neural networks by quantizing their weights and activations into multiple binary bases, known as multi-bit networks (MBNs), which accelerate the inference and reduce the storage for the deployment on low-resource mobile and embedded platforms. We propose Adaptive Loss-aware Quantization (ALQ), a new MBN quantization pipeline that is able to achieve an average bitwidth below one-bit without notable ...Conference Paper -
MapTransfer: Urban air quality map generation for downscaled sensor deployments
(2020)2020 IEEE/ACM Fifth International Conference on Internet-of-Things Design and Implementation (IoTDI)Dense deployments of commodity air quality sensors have proven effective to provide spatially-resolved information on urban air pollution in real-time. However, long-term operation of a dense sensor deployment incurs enormous maintenance expenses and efforts. A cost-effective alternative is to first collect measurements with an initial dense deployment and then rely on a small subset of sensors for air quality map generation. To avoid ...Conference Paper