文档章节

人工智能资料库:第65辑(20170805)

AllenOR灵感
 AllenOR灵感
发布于 2017/09/10 01:21
字数 741
阅读 1
收藏 0
点赞 0
评论 0

1.【Quora】Rank the most important factors during a PhD, which will increase your probability of finding a good faculty position?

简介:

A2A: I’s hard to make a simple rank-ordered list here because these factors combine in complicated, non-linear ways. So let me just say what we end up discussing in our faculty-hiring process in various departments in CMU SCS. Perhaps that will give you some idea about what you should work on.

原文链接:https://www.quora.com/Rank-the-most-important-factors-during-a-PhD-which-will-increase-your-probability-of-finding-a-good-faculty-position/answer/Scott-E-Fahlman?ref=fb_page


2.【博客】Faces recreated from monkey brain signals

简介:


The brains of primates can resolve different faces with remarkable speed and reliability, but the underlying mechanisms are not fully understood.

The researchers showed pictures of human faces to macaques and then recorded patterns of brain activity.

The work could inspire new facial recognition algorithms, they report.
In earlier investigations, Professor Doris Tsao from the California Institute of Technology (Caltech) and colleagues had used functional magnetic resonance imaging (fMRI) in humans and other primates to work out which areas of the brain were responsible for identifying faces.

Six areas were found to be involved, all of which are located in part of the brain known as the inferior temporal (IT) cortex. The researchers described these six areas as "face patches".

原文链接:http://www.bbc.com/news/science-environment-40131242


3.【论文】A Fast Unified Model for Parsing and Sentence Understanding

简介:

Tree-structured neural networks exploit valuable syntactic parse information as they interpret the meanings of sentences. However, they suffer from two
key technical problems that make them slow and unwieldy for large-scale NLP tasks: they usually operate on parsed sentences and they do not directly support batched computation. We address these issues by introducing the Stackaugmented Parser-Interpreter Neural Network (SPINN), which combines parsing and interpretation within a single treesequence hybrid model by integrating treestructured sentence interpretation into the
linear sequential structure of a shift-reduce parser. Our model supports batched computation for a speedup of up to 25× over other tree-structured models, and its integrated parser can operate on unparsed data with little loss in accuracy. We evaluate it on the Stanford NLI entailment task and show that it significantly outperforms other sentence-encoding models.

原文链接:https://arxiv.org/pdf/1603.06021.pdf


4.【博客】Hierarchical Softmax

简介:

Hierarchical softmax is an alternative to the softmax in which the probability of any one outcome depends on a number of model parameters that is only logarithmic in the total number of outcomes. In “vanilla” softmax, on the other hand, the number of such parameters is linear in the number of total number of outcomes. In a case where there are many outcomes (e.g. in language modelling) this can be a huge difference. The consequence is that models using hierarchical softmax are significantly faster to train with stochastic gradient descent, since only the parameters upon which the current training example depend need to be updated, and less updates means we can move on to the next training example sooner. At evaluation time, hierarchical softmax models allow faster calculation of individual outcomes, again because they depend on less parameters (and because the calculation using the parameters is just as straightforward as in the softmax case). So hierarchical softmax is very interesting from a computational point-of-view. By explaining it here, I hope to convince you that it is also interesting conceptually. To keep things concrete, I’ll illustrate using the CBOW learning task from word2vec (and fasttext, and others).

原文链接:http://building-babylon.net/2017/08/01/hierarchical-softmax/


5.【博客】How to Visualize Your Recurrent Neural Network with Attention in Keras

简介:


Neural networks are taking over every part of our lives. In particular — thanks to deep learning — Siri can fetch you a taxi using your voice; and Google can enhance and organize your photos automagically. Here at Datalogue, we use deep learning to structurally and semantically understand data, allowing us to prepare it for use automatically.
Neural networks are massively successful in the domain of computer vision. Specifically, convolutional neural networks(CNNs) take images and extract relevant features from them by using small windows that travel over the image. This understanding can be leveraged to identify objects from your camera (Google Lens) and, in the future, even drive your car (NVIDIA).

原文链接:https://medium.com/datalogue/attention-in-keras-1892773a4f22


本文转载自:http://www.jianshu.com/p/91a72437a1bf

共有 人打赏支持
AllenOR灵感
粉丝 10
博文 2634
码字总数 82983
作品 0
程序员
预测流行偏好,时尚 AI 未来可望取代造型师

【Technews科技新报】预测时尚潮流是一项需要天分的工作,还得仰赖一个庞大的系统让少数人追捧的时尚进入大众流行市场,进而让业者赚取大笔钞票。现在预测工作也可以交给人工智能,让服饰业者...

黄 嬿
2017/12/26
0
0
JavaAutoDeploy工具使用及BUG

JavaAutoDeploy工具使用及BUG 管理原理流程模型: 管理机安装好jdk环境 被管理机开启ssh及相应的端口 管理机新建代码存放目录 mkdir /data/release/20170805/app 把程序需要更新的代码及文件...

香小草
2017/12/29
0
0
人工智能知识整理-第1辑(20170603)-机器学习入门资源汇总

有一天我忽然忘记了一个函数的用法,于是就上谷歌搜,结果搜出来的竟然是自己写的一篇笔记,上面有很详细的回答。当时感觉是跟另外一个自己进行交流,那一个是刚学完知识,印象还非常深的自己...

人工智豪
2017/06/03
0
0
首期腾讯AI加速器毕业 9个月项目总估值翻3倍

  4月11日晚,首期腾讯AI加速器毕业典礼在重庆举行。从上千个国内AI创业项目中精选出25个项目以及从海外AI大赛选拔出的4个项目经过9个月加速,整体估值从70亿增至200多亿,翻了近3倍。其中...

机器之心
04/13
0
0
区块链技术让科学家共享患者健康资讯,同时保障个人资料安全

【Technews科技新报】目前医生在依据乳房摄影判断乳癌发生的情况下,有四分之一的乳癌无法被及时判断发现。为了提升乳癌确诊的效率,科学家计划以数百万包含了健康女性以及患有乳癌的女性乳房...

黄 斯沛
04/16
0
0
人工智能时代的工作、学习和生活---《人工智能》阅读笔记

自从“罗辑思维”栏目从优酷网站搬到得到APP并且变为每天几分钟的节目之后,我就很少收听它了。某天,我打开得到APP,并且点开了“罗辑思维”的节目清单,发现有一期的标题包含了“人工智能”...

zhouzxi
2017/07/15
0
0
人工智能、大数据、复杂系统学习

黑科技,人工智能前进之路势不可挡! “做大做强新兴产业集群,实施大数据发展行动,加强新一代人工智能研发应用。发展智能产业,拓展智能生活。” 人工智能已作为国家乃至全球新的经济增长动...

自学号
05/10
0
0
全球人工智能与机器人峰会首日议程公布:5段故事,致敬所有AI人

AI人,是一个值得敬畏的群体。 有的人,在AI一线奋战多年,65载如一日;有的人,获得世界最高荣誉后,仍自强不息…… 离6月29日开幕的第三届CCF-GAIR全球人工智能与机器人峰会,不到一个月的...

AI掘金志
06/06
0
0
人工智能有“天花板” 传统产业要“+科技”——知名企业家激战“新经济”

(原标题:人工智能有“天花板” 传统产业要“+科技”——知名企业家激战“新经济”) 中国证券网讯 据新华社12月5日消息,“携手新时代,共话新经济”,第四届世界互联网大会上,多位企业家...

上海证券报·中国证券网
2017/12/05
0
0
科学家说:AI有加强现存偏见的可能

桑斯坦在《网络共和国》当中提出了算法影响我们的认知世界、并在《信息乌托邦》当中第一次明确提出了算法使人形成“信息茧房”的危害。这是算法对于人脑的影响,而算法应用于人工智能中,也让...

玄学酱
04/13
0
0

没有更多内容

加载失败,请刷新页面

加载更多

下一页

Kafka设计解析(一)- Kafka背景及架构介绍

原创文章,转载请务必将下面这段话置于文章开头处。(已授权InfoQ中文站发布) 本文转发自技术世界,原文链接 http://www.jasongj.com/2015/03/10/KafkaColumn1 摘要   Kafka是由LinkedI...

mskk
8分钟前
0
0
使用Service Mesh整合您的微服务架构

在微服务架构的世界中,它正在达到这样的程度,即管理系统的复杂性对于利用它带来的好处变得至关重要。 目前,如何实现这些微服务不再是一个问题,因为有很多可用的框架(Spring Boot,Vert....

xiaomin0322
11分钟前
0
0
看看 LinkedList Java 9

终于迎来了 LinkedList 类,实现的接口就有点多了 Serializable, Cloneable, Iterable<E>, Collection<E>, Deque<E>, List<E>, Queue<E>。LinkedList是一个实现了List接口和Deque接口的双端链......

woshixin
30分钟前
0
0
算法 - 冒泡排序 C++

大家好,我是ChungZH。今天我给大家讲一下最基础的排序算法:冒泡排序(BubbleSort)。 冒泡排序算法的原理如下: 比较相邻的元素。如果第一个比第二个大(可以相反),就交换他们两个。 对每...

ChungZH
32分钟前
0
0
jquery ajax request payload和fromData请求方式

请求头的不同 fromData var data = { name : 'yiifaa'};// 提交数据$.ajax('app/', { method:'POST', // 将数据编码为表单模式 contentType:'application/x-ww...

lsy999
34分钟前
0
0
阿里P7架构师,带你点亮程序员蜕变之路

前言: Java是现阶段中国互联网公司中,覆盖度最广的研发语言。 掌握了Java技术体系,不管在成熟的大公司,快速发展的公司,还是创业阶段的公司,都能有立足之地。 有不少朋友问,成为Java架...

Java大蜗牛
36分钟前
1
0
Ecstore 在没有后台管理界面(维护)的情况如何更新表的字段

window 系统: 切换到:app\base 目录下: C:\Users\qimh>d: D:\>cd D:\WWW\huaqh\app\base 执行:D:\WWW\huaqh\app\base>cmd update linux 系统: 1># cd /alidata/www.novoeshop.com/app/......

qimh
40分钟前
0
0
设计模式-策略模式

策略模式 解释 对工厂模式的再次封装,使用参数控制上下文信息(将工厂返回的实例赋值给context field) 不会返回bean实例,只是设置对应的条件 调用context的方法(调用field的方法) 用户只...

郭里奥
43分钟前
0
0
python使用有序字典

python自带的collections包中有很多有用的数据结构可供使用,其中有个叫OrderedDict类,它可以在使用的时候记录元素插入顺序,在遍历使用的时候就可以按照原顺序遍历。 a = {"a":1,"b"...

芝麻糖人
今天
0
0
RestTemplate HttpMessageConverter

RestTemplate 微信接口 text/plain HttpMessageConverter

微小宝
今天
0
0

没有更多内容

加载失败,请刷新页面

加载更多

下一页

返回顶部
顶部