32 citations · 78 across the 9 of their papers we have counts for
10 papers
Localised Adaptive Spatial-Temporal Graph Neural Network
Wenying Duan, Xiaoxi He, Zimu Zhou +2
Spatial-temporal graph models are prevailing for abstracting and modelling spatial and temporal dependencies. In this work, we ask the following question: whether and to what exten…
Towards Capacity-Aware Broker Matching: From Recommendation to Assignment
Shuyue Wei, Yongxin Tong, Zimu Zhou +4
Online real estate platforms are gaining increasing popularity, where a central issue is to match brokers with clients for potential housing transactions. Mainstream platforms matc…
AdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices
Sicong Liu, Xiaochen Li, Zimu Zhou +4
The ubiquity of camera-embedded devices and the advances in deep learning have stimulated various intelligent mobile video applications. These applications often demand on-device p…
p-Meta: Towards On-device Deep Model Adaptation
Zhongnan Qu, Zimu Zhou, Yongxin Tong +1
Data collected by IoT devices are often private and have a large diversity across users. Therefore, learning requires pre-training a model with available representative data sample…
Adaptive Task Planning for Large-Scale Robotized Warehouses
Dingyuan Shi, Yongxin Tong, Zimu Zhou +3
Robotized warehouses are deployed to automatically distribute millions of items brought by the massive logistic orders from e-commerce. A key to automated item distribution is to p…
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles
Sicong Liu, Junzhao Du, Kaiming Nan +3
Recent breakthroughs in Deep Neural Networks (DNNs) have fueled a tremendously growing demand for bringing DNN-powered intelligence into mobile platforms. While the potential of de…
Adaptive Loss-aware Quantization for Multi-bit Networks
Zhongnan Qu, Zimu Zhou, Yun Cheng +1
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…
Pruning-Aware Merging for Efficient Multitask Inference
Xiaoxi He, Dawei Gao, Zimu Zhou +2
Many mobile applications demand selective execution of multiple correlated deep learning inference tasks on resource-constrained platforms. Given a set of deep neural networks, eac…
Multi-Task Zipping via Layer-wise Neuron Sharing
Xiaoxi He, Zimu Zhou, Lothar Thiele
Future mobile devices are anticipated to perceive, understand and react to the world on their own by running multiple correlated deep neural networks on-device. Yet the complexity…
DorFin: WiFi Fingerprint-based Localization Revisited
Chenshu Wu, Zheng Yang, Zimu Zhou +2
Although WiFi fingerprint-based indoor localization is attractive, its accuracy remains a primary challenge especially in mobile environments. Existing approaches either appeal to…