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FEDERATED DOUBLY STOCHASTIC KERNEL LEARNING ON VERTICAL PARTITIONED DATA

机译:联合垂直分区数据的双随机内核学习

摘要

System and method for prediction using a machine learning model. The system includes a coordinator, an active computing device and a passive computing device in communication with each other. The active computing device has a processor and a storage device storing computer executable code. The computer executable code is configured to: obtain parameters of the machine learning model; retrieve an instance from the local data; sample a random direction of the instance; compute a dot product of the random direction and the instance, and calculate a random feature; compute predicted values of the instance in the active and passive computing devices and summarize them to obtain a final predicted value; determine a model coefficient using the random feature, the final predicted value, and a target value of the instance; update the machine learning model using the model coefficient; and predict a value for a new instance.
机译:使用机器学习模型预测的系统和方法。 该系统包括协调器,有源计算设备和彼此通信的被动计算设备。 活动计算设备具有存储器和存储计算机可执行代码的存储设备。 计算机可执行代码配置为:获取机器学习模型的参数; 从本地数据检索实例; 样本实例的随机方向; 计算随机方向和实例的点乘积,并计算随机特征; 计算主动和被动计算设备中实例的预测值,并汇总它们以获得最终预测值; 使用随机功能,最终预测值和实例的目标值确定模型系数; 使用模型系数更新机器学习模型; 并预测新实例的值。

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