基于因子分解的隐层变量学习,应用于短语句语种识别模型的自适应     LFVs(Language Feature Vectors,语种特征向量)[11],与BSVs(Bottleneck Speaker Vectors)类似,即瓶颈特征     3.1. 神经元调制 由于说话人特性的变化反映在语音信号中,因此将表示说话人适应声学特性的特征拼接到特征中.如VTLN或fMLLR,是直接对声学特征进行操作的自适应方法.可以训练一个说话人自适应系统以基于说话人属性直接对输入特征进行转换,这样效果与基于i…
参考 1. 基础模型(Basic Model) Sequence to sequence模型(Seq2Seq) 从机器翻译到语音识别方面都有着广泛的应用. 举例: 该机器翻译问题,可以使用"编码网络(encoder network)"+"解码网络(decoder network)"两个RNN模型组合的形式来解决. encoder network将输入语句编码为一个特征向量,传递给decoder network,完成翻译.具体模型结构如下图所示: 其中,encoder…
ICLR 2013 International Conference on Learning Representations May 02 - 04, 2013, Scottsdale, Arizona, USA ICLR 2013 Workshop Track Accepted for Oral Presentation Zero-Shot Learning Through Cross-Modal Transfer Richard Socher, Milind Ganjoo, Hamsa Sr…
Machine and Deep Learning with Python Education Tutorials and courses Supervised learning superstitions cheat sheet Introduction to Deep Learning with Python How to implement a neural network How to build and run your first deep learning network Neur…
Deep Learning in a Nutshell: History and Training This series of blog posts aims to provide an intuitive and gentle introduction to deep learning that does not rely heavily on math or theoretical constructs. The first part in this series provided an…
Machine Learning for Developers Most developers these days have heard of machine learning, but when trying to find an 'easy' way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learnin…
https://www.quora.com/How-do-I-learn-machine-learning-1?redirected_qid=6578644   How Can I Learn X? Learning Machine Learning Learning About Computer Science Educational Resources Advice Artificial Intelligence How-to Question Learning New Things Lea…
Ensemble Methods for Deep Learning Neural Networks to Reduce Variance and Improve Performance 2018-12-19 13:02:45 This blog is copied from: https://machinelearningmastery.com/ensemble-methods-for-deep-learning-neural-networks/ Deep learning neural ne…
Understanding, generalisation, and transfer learning in deep neural networks FEBRUARY 27, 2017   This is the first in a series of posts looking at the ‘top 100 awesome deep learning papers.’ Deviating from the normal one-paper-per-day format, I’ll ta…
Rolling in the Deep (Learning) Deep Learning has been getting a lot of press lately, and is one of the hottest the buzz terms in Tech these days. Just check out one of the few recent headlines from Forbes, MIT Tech Review and you will surely see thes…
About this Course If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "s…
最近在学深度学习相关的东西,在网上搜集到了一些不错的资料,现在汇总一下: Free Online Books  by Yoshua Bengio, Ian Goodfellow and Aaron Courville Neural Networks and Deep Learning42 by Michael Nielsen Deep Learning27 by Microsoft Research Deep Learning Tutorial23 by LISA lab, University…
转自:https://github.com/terryum/awesome-deep-learning-papers Awesome - Most Cited Deep Learning Papers A curated list of the most cited deep learning papers (since 2010) I believe that there exist classic deep learning papers which are worth reading re…
Final Version 1.1 Date Issued:            13 March 2012 Latest version:         http://www.imsglobal.org/lti/ IPR and Distribution Notices Recipients of this document are requested to submit, with their comments, notification of any relevant patent c…
课程主页:http://cs231n.stanford.edu/   Introduction to neural networks -Training Neural Network ______________________________________________________________________________________________________________________________________________________________…
DEEP LEARNING WITH STRUCTURE Charlie Tang is a PhD student in the Machine Learning group at the University of Toronto, working with Geoffrey Hinton and Ruslan Salakhutdinov, whose research interests include machine learning, computer vision and cogni…
Teaching Your Computer To Play Super Mario Bros. – A Fork of the Google DeepMind Atari Machine Learning Project Posted by ehrenbrav on August 25, 2016Leave a comment (14)Go to comments   For those who want to get right to the good stuff, the installa…
Deep Learning and the Triumph of Empiricism By Zachary Chase Lipton, July 2015 Deep learning is now the standard-bearer for many tasks in supervised machine learning. It could also be argued that deep learning has yielded the most practically useful…
Deep Learning论文笔记之(八)Deep Learning最新综述 zouxy09@qq.com http://blog.csdn.net/zouxy09 自己平时看了一些论文,但老感觉看完过后就会慢慢的淡忘,某一天重新拾起来的时候又好像没有看过一样.所以想习惯地把一些感觉有用的论文中的知识点总结整理一下,一方面在整理过程中,自己的理解也会更深,另一方面也方便未来自己的勘察.更好的还可以放到博客上面与大家交流.因为基础有限,所以对论文的一些理解可能不太正确,还望大家不吝指正交流,谢谢.…
Introduction Deep learning is a recent trend in machine learning that models highly non-linear representations of data. In the past years, deep learning has gained a tremendous momentum and prevalence for a variety of applications (Wikipedia 2016a).…
在总结正则化(Regularization)之前,我们先谈一谈正则化是什么,为什么要正则化. 个人认为正则化这个字眼有点太过抽象和宽泛,其实正则化的本质很简单,就是对某一问题加以先验的限制或约束以达到某种特定目的的一种手段或操作.在算法中使用正则化的目的是防止模型出现过拟合.一提到正则化,很多同学可能马上会想到常用的L1范数和L2范数,在汇总之前,我们先看下LP范数是什么鬼. LP范数 范数简单可以理解为用来表征向量空间中的距离,而距离的定义很抽象,只要满足非负.自反.三角不等式就可以称之为距离…
Complete Small Focused Projects and Demonstrate Your Skills (完成小型针对性机器学习项目,证明你的能力) A portfolio is typically used by designers and artists to show examples of prior work to prospective clients and employers. Design, art and photography are examples wh…
What's the most effective way to get started with deep learning?       29 Answers     Yoshua Bengio, My lab has been one of the three that started the deep learning approach, back in 2006, along with Hinton's... Answered Jan 20, 2016   Originally Ans…
Learning Deep Learning with Keras Piotr Migdał - blog Projects Articles Publications Resume About Photos Learning Deep Learning with Keras 30 Apr 2017 • Piotr Migdał • [machine-learning] [deep-learning] [overview] I teach deep learning both for a liv…
this blog from: https://github.com/LantaoYu/MARL-Papers Paper Collection of Multi-Agent Reinforcement Learning (MARL) This is a collection of research and review papers of multi-agent reinforcement learning (MARL). The sharing principle of these refe…
A Gentle Guide to Machine Learning Machine Learning is a subfield within Artificial Intelligence that builds algorithms that allow computers to learn to perform tasks from data instead of being explicitly programmed. Got it? We can make machines lear…
My deep learning reading list 主要是顺着Bengio的PAMI review的文章找出来的.包括几本综述文章,将近100篇论文,各位山头们的Presentation.全部都可以在google上找到.BTW:由于我对视觉尤其是检测识别比较感兴趣,所以关于DL的应用主要都是跟Vision相关的.在其他方面比如语音或者NLP,很少或者几乎没有.个人非常看好CNN和Sparse Autoencoder,这个list也反映了我的偏好,仅供参考. Review Book Lis…
最近开始学习深度学习了,加油! 下文转载自:http://blog.sina.com.cn/s/blog_bda0d2f10101fpp4.html 主要是顺着Bengio的PAMI review的文章找出来的.包括几本综述文章,将近100篇论文,各位山头们的Presentation.全部都可以在google上找到. BTW:由于我对视觉尤其是检测识别比较感兴趣,所以关于DL的应用主要都是跟Vision相关的.在其他方面比如语音或者NLP,很少或者几乎没有.个人非常看好CNN和Sparse Au…
Deep Learning Libraries by Language Tweet         Python Theano is a python library for defining and evaluating mathematical expressions with numerical arrays. It makes it easy to write deep learning algorithms in python. On the top of the Theano man…
DML学习原文链接:http://blog.csdn.net/lzt1983/article/details/7884553 一篇metric learning(DML)的综述文章,对DML的意义.方法论和经典论文做一个介绍,同时对我的研究经历和思考做一个总结.可惜一直没有把握自己能够写好,因此拖到现在. 先列举一些DML的参考资源,以后有时间再详细谈谈. 1. Wikipedia 2. CMU的Liu Yang总结的关于DML的综述页面.对DML的经典算法进行了分类总结,其中她总结的论文非常有…