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Machine Learning No.5: Neural networks

1. advantage: when number of features is too large, so previous algorithm is not a good way to learn complex nonlinear hypotheses. 2. representation "activation" of unit i in layer j matrix of weights controlling function mapping from layer j to…

[Machine Learning]学习笔记-Neural Networks

引子 对于一个特征数比较大的非线性分类问题,如果采用先前的回归算法,需要很多相关量和高阶量作为输入,算法的时间复杂度就会很大,还有可能会产生过拟合问题,如下图: 这时就可以选择采用神经网络算法. 神经网络算法最早是人们希望模仿大脑的学习功能而想出来的. 一个神经元,有多个树突(Dendrite)作为信息的输入通道,也有多个轴突(Axon)作为信息的输出通道.一个神经元的输出可以作为另一个神经元的输入.神经元的概念和多分类问题的分类器概念很相近,都是可以接收多个输入,在不同的权值(weights)…

（转）Understanding, generalisation, and transfer learning in deep neural networks

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[译]深度神经网络的多任务学习概览(An Overview of Multi-task Learning in Deep Neural Networks)

译自:http://sebastianruder.com/multi-task/ 1. 前言 在机器学习中,我们通常关心优化某一特定指标,不管这个指标是一个标准值,还是企业KPI.为了达到这个目标,我们训练单一模型或多个模型集合来完成指定得任务.然后,我们通过精细调参,来改进模型直至性能不再提升.尽管这样做可以针对一个任务得到一个可接受得性能,但是我们可能忽略了一些信息,这些信息有助于在我们关心的指标上做得更好.具体来说,这些信息就是相关任务的监督数据.通过在相关任务间共享表示信息,我们的模型在…

DAG-GNN: DAG Structure Learning with Graph Neural Networks

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论文笔记之：Learning Multi-Domain Convolutional Neural Networks for Visual Tracking

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[CVPR2015] Is object localization for free? – Weakly-supervised learning with convolutional neural networks论文笔记

p.p1 { margin: 0.0px 0.0px 0.0px 0.0px; font: 13.0px "Helvetica Neue"; color: #323333 } p.p2 { margin: 0.0px 0.0px 0.0px 0.0px; font: 13.0px "Helvetica Neue"; color: #042eee } span.s1 { } span.s2 { text-decoration: underline } Is objec…

Machine Learning, Homework 9, Neural Nets

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This instability is a fundamental problem for gradient-based learning in deep neural networks. vanishing exploding gradient problem

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【论文阅读】Learning Dual Convolutional Neural Networks for Low-Level Vision

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