DL4J Distributed Training: Technical Explanation Asynchronous SGD Implementation Strom’s Approach DL4J’s ASGD implementation Plain Mode vs Mesh Mode Encoding Schemes Parameter...

LocalResponseNorm 参数 形状 代码示例 LocalResponseNorm paddle.nn.LocalResponseNorm ( size, alpha=0.0001, beta=0.75, k=1.0, data_format=’NCHW’, name=None ) [源代码] 局部响应正则化（Local Res...

bpr_loss bpr_loss paddle.fluid.layers.bpr_loss ( input, label, name\=None ) [源代码] 贝叶斯个性化排序损失函数（Bayesian Personalized Ranking Loss Operator ） 该OP属于pairwise类型的损失函数。损失值由下式计算而得...

SketchRnn Description Quickstart Usage Initialize Parameters Properties .ready Methods .reset() .generate() Examples Demo Tutorials Acknowledgements Source Code ...

5、神经网络 上篇主要讨论了决策树算法。首先从决策树的基本概念出发，引出决策树基于树形结构进行决策，进一步介绍了构造决策树的递归流程以及其递归终止条件，在递归的过程中，划分属性的选择起到了关键作用，因此紧接着讨论了三种评估属性划分效果的经典算法，介绍了剪枝策略来解决原生决策树容易产生的过拟合问题，最后简述了属性连续值/缺失值的处理方法。本篇将讨论现阶段...

Getting Started with Katib Katib setup Installing Katib Setting up persistent volumes Accessing the Katib UI Examples Example using random algorithm TensorFlow example PyTorc...

Installing plugins Managing plugins List Usage Example List (with CAT API) Usage Example response Install Install a plugin by name Usage Example Install a plugin from a ...

Trains two recurrent neural networks based upon a story and a question. Notes Trains two recurrent neural networks based upon a story and a question. The resulting merged vect...

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二、FNN 2.1 模型 2.1.1 FNN 2.1.2 SNN 2.2 实验 二、FNN 传统的 CTR 预估模型大多数采用线性模型。线性模型的优点是易于实现，缺点是：模型表达能力较差，无法学习特征之间的相互作用 interaction 。 非线性模型（如：FM,GBDT ）能够利用不同的组合特征，因此能够改善模型的表达能力。但是这...