Problem: time series forecasting Challenge: forecasting for non-stationary signals and multiple future steps prediction ?? how to deal with non-stationary datasets?? Introduction one-step prediction problem VS multi-step prediction; multi-step foreca…

From: Yoshua Bengio Problem: time series forecasting. Supplementary knowledge: 1. what is meta-learning: https://www.zhihu.com/question/264595128 2. what is zero-shot learning: ZSL就是希望我们的模型能够对其从没见过的类别进行分类,让机器具有推理能力,实现真正的智能.其中零次(Zero-shot)是指对于要分类的类别对象…

https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet Machine Learning made for .NET ML.NET is a machine learning framework built for .NET developers. Use your .NET and C# or F# skills to easily integrate custom machine learning…

 Summary on deep learning framework --- Theano && Lasagne 2017-03-23 1. theano.function output = input ** 2  f = theano.function([input], output) print(f(3)) >> the output is: 3^2 = 9. 2.  verbose = 1 or 0, does it have any difference ?   so…

Meta Learning/ Learning to Learn/ One Shot Learning/ Lifelong Learning 2018-08-03 19:16:56 本文转自:https://github.com/floodsung/Meta-Learning-Papers 1 Legacy Papers [1] Nicolas Schweighofer and Kenji Doya. Meta-learning in reinforcement learning. Neural…

郑重声明:原文参见标题,如有侵权,请联系作者,将会撤销发布! Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong. 2019. Federated Machine Learning: Concept and Applications. ACM Trans. Intell. Syst. Technol. 10, 2, Article 12 (February 2019), 19 pages. https://doi.org/0000001.0…

Co-saliency Detection via A Self-paced Multiple-instance Learning Framework  T-PAMI  2016  摘要:Co-saliency detection 从一组图像中提取出共同显著的物体.一方面,传统的检测方法严重依赖于手工设计的距离度量来反应协同显著区域有效的属性.另一方面,大部分的当前方法都是无监督的.在实际场景中,效果不会很好,因为缺乏一种 robust 的学习机制 来充分利用每一张图像的 weak labels…

Getting Started with Zend Framework MVC Applications This tutorial is intended to give an introduction to using Zend Framework 2 by creating a simple database driven application using the Model-View-Controller paradigm. By the end you will have a wor…

Summary on deep learning framework --- PyTorch  Updated on 2018-07-22 21:25:42  import osos.environ["CUDA_VISIBLE_DEVICES"]="4" 1. install the pytorch version 0.1.11  ## Version 0.1.11 ## python2.7 and cuda 8.0 sudo pip install http://…

 Summary on deep learning framework --- TensorFlow Updated on 2018-07-22 21:28:11 1. Check failed: s.ok() could not find cudnnCreate in cudnn DSO;  tensorflow/stream_executor/cuda/cuda_dnn.cc:221] Check failed: s.ok() could not find cudnnCreate in cu…

Summary on deep learning framework --- Torch7  2018-07-22 21:30:28 1. 尝试第一个 CNN 的 torch版本, 代码如下: -- We now have 5 steps left to do in training our first torch neural network -- 1. Load and normalize data -- 2. Define Neural Network -- 3. Define Loss…

原文链接:Meta Learning单排小教学 虽然Meta Learning现在已经非常火了,但是还有很多小伙伴对于Meta Learning不是特别理解.考虑到我的这个AI游乐场将充斥着Meta Learning的分析解读及各种原创思考,所以今天Flood就和大家做一个Meta Learning小教学,希望能够用最简短,最通俗的语言来让大家明白Meta Learning的概念,Meta Learning的几种研究方法,以及Meta Learning未来的发展,带大家上分!相信这个Meta L…

Visual Question Answering as a Meta Learning Task ECCV 2018 2018-09-13 19:58:08 Paper: http://openaccess.thecvf.com/content_ECCV_2018/papers/Damien_Teney_Visual_Question_Answering_ECCV_2018_paper.pdf 1. Introduction: 本文提出一种新的 VQA 思路,将 meta-learning 结…

深度学习课程笔记(十七)Meta-learning (Model Agnostic Meta Learning) 2018-08-09 12:21:33 The video tutorial can be found from: Model Agnostic Meta Learning Related Videos: My talk for Model Agnostic Meta Learning with domain adaptation Paper: https://arxiv.org/p…

Deep Meta Learning for Real-Time Visual Tracking based on Target-Specific Feature Space  2018-01-04  15:58:15  写在前面:为什么要看这个paper?这篇 paper 貌似是第一个将 meta-learning 应用到 visual tracking 领域的,取得了速度和精度较好的平衡. Introduction: 我们知道,tracking 中比较重要的就是 target object…

Deep Learning framework --- MexNet 安装,测试,以及相关问题总结  一.安装:   参考博文:http://www.open-open.com/lib/view/open1448030000650.html  Note: gcc g++ 需要 4.8 版本. 二.…

Install and Compile MatConvNet: CNNs for MATLAB --- Deep Learning framework 2017-04-18  10:19:35 If you want to use matlab convnet, you just install according to the following tutorials: 1. Download and unzip the original source file from: http://www…

Foundations of Machine Learning: The PAC Learning Framework(2) (一)假设集有限在一致性下的学习界. 在上一篇文章中我们介绍了PAC-learnable的定义,以及证明了一个例子是PAC-learnable. 这一节我们介绍当hypothesis set是有限时,且算法$\mathcal{A}$相对与样本S满足一致性条件下的PAC问题.下一节介绍不一致条件下的PAC问题. 一致性(consistent):如果一个算法产生的假设$h_s…

写在最前:本系列主要是在阅读 Mehryar Mohri 等的最新书籍<Foundations of Machine Learning>以及 Schapire 和 Freund 的 <Boosting: Foundations and Algorithms>过程中所做的笔记.主要讨论三个部分的内容.第一部分是PAC的基本概念,介绍了泛化误差和经验误差,并且讨论了假设集$H$有限时的泛化边界.第二部分介绍了假设集$H$无限时的泛化边界,引入了三种衡量$H$复杂程度的机制,分别是Rad…

The Rise of Meta Learning 2019-10-18 06:48:37 This blog is from: https://towardsdatascience.com/the-rise-of-meta-learning-9c61ffac8564 Connor Shorten Follow Oct 16 · 9 min read   https://openai.com/blog/solving-rubiks-cube/ Meta-Learning describes th…

MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning 2019-08-11 19:48:17 Paper: https://arxiv.org/pdf/1903.10258.pdf Code: https://github.com/liuzechun/MetaPruning 1. Background and Motivation:…

Problem: multi-horizon probabilistic forecasting tasks; Propose an end-to-end framework for multi-horizon time series forecasting, with temporal attention mechanisms to capture latent patterns. Introduction: forecasting ----- understanding demands. t…

MetaPruning 2019-ICCV-MetaPruning Meta Learning for Automatic Neural Network Channel Pruning Zechun Liu (HKUST).Xiangyu Zhang (MEGVII).Jian Sun(MEGVII) GitHub:251 stars Citation:20 Motivation A typical pruning approach contains three stages: training…

Motivation: The lack of transparency of the deep  learning models creates key barriers to establishing trusts to the model or effectively troubleshooting classification errors Common methods on non-security applications: forward propagation / back pr…

摘要 新闻推荐系统中,新闻具有很强的动态特征(dynamic nature of news features),目前一些模型已经考虑到了动态特征. 一:他们只处理了当前的奖励(ctr);. 二:有一些模型利用了用户的反馈,如用户返回的频率.(user feedback other than click / no click labels (e.g., how frequentuser returns) ); 三:会给用户推送一些内容类似的新闻,用户看多了会无聊. 为了解决上述问题,我们提出了DQ…

目录 元学习(Meta-learning) 元学习被用在了哪些地方? Few-Shot Learning(小样本学习) 最近的元学习方法如何工作 Model-Agnostic Meta-Learning (MAML) 元学习(Meta-learning) 智能的一个关键方面是多功能性--做许多不同事情的能力.当前的AI系统可以做到精通于某一项技能,但是,如果我们要求AI系统执行各种看似简单的问题(用同一个模型去解决不同问题),它将会变得十分困难.相反,人类可以明智地利用以往经验并采取行动以适应各…

常用的deep learning frameworks 基本转自:http://www.codeceo.com/article/10-open-source-framework.html 1. Caffe 基于C++开发 2. Theano 大部分代码是使用CYthon开发的,主页有很详细的教程,在github上有Theano的软件包,另外还有一份pdf的tutorial 基于theano派生了许多的深度学习python软件包:Keras(documents).Lasagne(documents…

Learning to Learn Chelsea Finn    Jul 18, 2017 A key aspect of intelligence is versatility – the capability of doing many different things. Current AI systems excel at mastering a single skill, such as Go, Jeopardy, or even helicopter aerobatics. But…

题记:最近在做LLL(Life Long Learning),接触到了SSL(Semi-Supervised Learning)正好读到了谷歌今年的论文,也是比较有点开创性的,浅显易懂,对比实验丰富,非常适合缺乏基础科学常识和刚刚读研不会写论文的同学读一读,触类旁通嘛. 这篇论文思路等等也非常适合刚刚开始做学术时候写文论参考使用,你看,它有创造性(半监督学习用在了目标检测上),理论基础扎实(体现在专业词汇丰富,也介绍了其他相关论文,做个小综述论文都够了),工作量够够的(大量的对比试验),实验效果…

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