1 - 6 of 6 Chapters
[In this chapter, we introduce the background of Internet-of-Things (IoT) system and discuss the three major technology layers in IoT. Furthermore, we discuss the machine learning based data analytics techniques from both the algorithm perspective and computation perspective. As the increasing...
[In this chapter, edge computing on IoT devices is firstly discussed to achieve low-latency, energy efficient, private and scalable computation. Then we use IoT based smart buildings as one example to illustrate the edge computing in IoT system for applications such as indoor positioning, energy...
[This chapter presents a least-square based learning on the single hidden layer neural network. A square-root free Cholesky decomposition technique is applied to reduce the training complexity. Furthermore, the optimized learning algorithm is mapped on CMOS and RRAM based hardware. The two...
[This chapter introduces a tensorized formulation for compressing neural network during training. By reshaping neural network weight matrices into high dimensional tensors with low-rank decomposition, significant neural network compression can be achieved with maintained accuracy. A layer-wise...
[In this chapter, we discuss the application of distributed machine learning techniques for indoor data analytics on smart-gateway network. More specifically, this chapter investigates three IoT applications, which are indoor positioning system, energy management system and network intrusion...
[The Internet of things (IoT) is to use networked objects with intelligence to improve resource efficiency. A typical IoT system can sense data from real-world, use sensed information to reason the environment and then perform the desired action. The intelligence of IoT systems comes from...
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