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Data poisoning attack of recommend system using the algorithm of MF.
请问您那边的结果是正常的吗
compute_grad.py中的第五十行,按照我的理解,应该是
u_m = user_features_.take(m, axis = 0)
而不是
u_m = user_features_.take(i, axis = 0)
作者您好,原文中用μ1和μ2来权衡对于推荐系统可用性和完整性的攻击,代码中是否没有这部分呢
作者你好,我有两个问题:
主函数中:
for t in xrange(m_iters):
...
grad_total = compute_grad(...)
看起来主函数中只是计算了梯度,似乎没有更新的步骤?
另外:
mal_data += grad_total * s_t[t]
mal_data[mal_data > Lamda] = Lamda
mal_data[mal_data < - Lamda] = - Lamda
计算RMSE之前,这几步操作是什么含义能解释下吗?
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