Wearable medical devices with sensor continuously generate enormous data which is often
called as big data mixed with structured and unstructured data. Due to the complexity of the …

Nowadays, wearable medical devices play a vital role in many environments such as
continuous health monitoring of individuals, road traffic management, weather forecasting …

As wearable medical sensors continuously generate enormous data, it is difficult to process
and analyse. This paper focuses on developing scalable sensor data processing …

We consider federated learning in tiered communication networks. Our network model
consists of a set of silos, each holding a vertical partition of the data. Each silo contains a …

Despite the importance of sparsity in many large-scale applications, there are few methods
for distributed optimization of sparsity-inducing objectives. In this paper, we present a …

The most critical objective in security surveillance is abnormal event detection in public
scenarios. A scheme is presented for detecting abnormal behaviours in the activities of …

带有传感器的可穿戴式医疗设备不断生成大量数据, 由于数据的复杂性, 难以通过处理和分析大
数据来找到有价值的决策信息. 为了解决这个问题, 提出一种新的物联网体系结构 …

摘要由于生物信息学, 心理学诊断, 计算语言与语音学, 计算机视觉, 门户网站, 电子商务,
移动互联网, 物联网中处理高维和超高维数据的需求不断涌现, 迫切需要研究具有变量选择和 …

In this paper, we study the distributed logistic regression to process the separated large
scale data which is stored in different linked computers. Based on the Alternating Direction …

The distributed alternating direction method of multipliers is an effective method to solve
large-scale machine learning. At present, most distributed ADMM algorithms need to transfer …