三重损失反向传播梯度公式是什么?

本文介绍了三重损失反向传播梯度公式是什么?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我正在尝试使用 caffe 来实现

渐变 w.r.t 锚"输入 (fa):

梯度 w.r.t 正"输入 (fp):

梯度 w.r.t 负"输入 (fn):

原来的计算(我出于感情原因离开这里……)

请参阅评论 更正最后一项.

I am trying to use caffe to implement triplet loss described in Schroff, Kalenichenko and Philbin "FaceNet: A Unified Embedding for Face Recognition and Clustering", 2015.

I am new to this so how to calculate the gradient in back propagation?

解决方案

I assume you define the loss layer as

layer { name: "tripletLoss" type: "TripletLoss" bottom: "anchor" bottom: "positive" bottom: "negative" ... }

Now you need to compute a gradient w.r.t each of the "bottom"s.

The loss is given by:

The gradient w.r.t the "anchor" input (fa):

The gradient w.r.t the "positive" input (fp):

The gradient w.r.t the "negative" input (fn):

The original calculation (I leave here for sentimental reasons...)

Please see comment correcting the last term.