1.Information publication:sigir 2011 author:Jing Liu Harbin Institute of TechnologyMicrosoft Research Asia 2.What 在CQA(community of question and answer)中衡量user 的experise score,给出了两种衡量模型:1, TrueSkill;  2, SVM Model 3.Dataset NTCIR-8 CQA 数据地址: arch.nii…

中文简单介绍: 本文对怎样在问答社区对用户主题兴趣及专业度建模分析进行了研究,而且提出了针对此问题的统计图模型Topics Expertise Model. 论文出处:CIKM'13. 英文摘要: Community Question Answering (CQA) websites, where people share expertise on open platforms, have become large repositories of valuable knowledge. To b…

Awesome Works  !!!! Table of Contents Conference Papers 2017 ICCV 2017 CVPR 2017 Others 2016 ECCV 2016 CVPR 2016 Others 2015 ICCV 2015 CVPR 2015 Others 2014 CVPR 2014 Others & Before Journal Papers Theses Datasets Challenges Other Related Papers Eval…

Large Scale Visual Recognition Challenge 2015 (ILSVRC2015) Legend: Yellow background = winner in this task according to this metric; authors are willing to reveal the method White background = authors are willing to reveal the method Grey background…

@http://www-cs-faculty.stanford.edu/people/karpathy/cvpr2015papers/ CVPR 2015 papers (in nicer format than this) maintained by @karpathy NEW: This year I also embedded the (1,2-gram) tfidf vectors of all papers with t-sne and placed them in an interf…

https://www.fdic.gov/regulations/examinations/credit_card/ch8.html Types of Scoring FICO Scores    VantageScore    Other Scores              Application Scoring              Attrition Scoring              Bankruptcy Scoring              Behavior Scor…

Gartner 2018 年WAF魔力象限报告:云WAF持续增长,Bot管理与API安全拥有未来 来源 https://www.freebuf.com/articles/paper/184903.html AngelaY  2018-09-19  *AngelaY 编译整理,转载请注明来自 FreeBuf.COM 8 月 29 日,Gartner 发布 2018 年度 Web 应用防火墙(WAF)魔力象限,这是 Gartner 自 2014 年之后连续第五年发布此类报告.报告中照例描述了全球 W…

This article come from HEREARS-L1: Learning Tuesday 10:30–12:30; Oral Session; Room: Leonard de Vinci 10:30  ARS-L1.1—GROUP STRUCTURED DIRTY DICTIONARY LEARNING FOR CLASSIFICATION Yuanming Suo, Minh Dao, Trac Tran, Johns Hopkins University, USA; Hojj…

Exploring the 7 Different Types of Data Stories What makes a story truly data-driven? For one, the numbers aren’t caged in a sidebar graph. Instead, the data helps drive the narrative. Data can help narrate as many types of stories as there are angle…

[root@localhost tt]# man listen LISTEN() Linux Programmer’s Manual LISTEN() NAME listen - listen for connections on a socket SYNOPSIS #include <sys/socket.h> int listen(int sockfd, int backlog); DESCRIPTION To accept connections, a socket ), a willi…

B. Qualifying Contest 题目链接http://codeforces.com/contest/659/problem/B Description Very soon Berland will hold a School Team Programming Olympiad. From each of the m Berland regions a team of two people is invited to participate in the olympiad. The q…

time limit per test 1 second memory limit per test 256 megabytes input standard input output standard output Very soon Berland will hold a School Team Programming Olympiad. From each of the m Berland regions a team of two people is invited to partici…

欢迎大家前往云+社区,获取更多腾讯海量技术实践干货哦~ 决策树可能会受到高度变异的影响,使得结果对所使用的特定测试数据而言变得脆弱. 根据您的测试数据样本构建多个模型(称为套袋)可以减少这种差异,但是树本身是高度相关的. 随机森林是套袋(方法)的延伸,除了基于多个测试数据样本构建树木之外,它还限制了可用于构建树木的特征,使得树木间具有差异.这反过来可以提升算法的表现. 在本教程中,您将了解如何在Python中从头开始实现随机森林算法. 完成本教程后,您将知道: 套袋决策树和随机森林算法的区别.…

Qualifying Contest CodeForces - 659B Very soon Berland will hold a School Team Programming Olympiad. From each of the mBerland regions a team of two people is invited to participate in the olympiad. The qualifying contest to form teams was held and i…

Person Re-identification with Deep Similarity-Guided Graph Neural Network 2018-07-27 17:41:45 Paper: https://128.84.21.199/pdf/1807.09975.pdf 本文将 Graph Neural Network (GNN) 应用到 person re-ID 的任务中,用于 model 不同 prob-gallery 之间的关系,将该信息也用于 feature learning…

If you see a package or project here that is no longer maintained or is not a good fit, please submit a pull request to improve this file. Thank you! Contents Awesome Go Audio and Music Authentication and OAuth Command Line Configuration Continuous I…

AC actual cost 实际成本 ACWP actual cost of work performed 已完工作实际成本 BAC budget at completion 完工预算 BCWP budgeted cost of work performed 已完工作预算成本 BCWS budgeted cost of work scheduled 计划工作预算成本 CCB change control board 变更控制委员会 COQ cost of quality 质量成本 CPAF c…

My Brute Time Limit: 2000/1000 MS (Java/Others)    Memory Limit: 32768/32768 K (Java/Others) Total Submission(s): 941    Accepted Submission(s): 372 Problem Description Seaco is a beautiful girl and likes play a game called "My Brute". Before Va…

B. Qualifying Contest 题目连接: http://www.codeforces.com/contest/659/problem/B Description Very soon Berland will hold a School Team Programming Olympiad. From each of the m Berland regions a team of two people is invited to participate in the olympiad.…

B. Qualifying Contest time limit per test 1 second memory limit per test 256 megabytes input standard input output standard output Very soon Berland will hold a School Team Programming Olympiad. From each of the m Berland regions a team of two people…

题目链接: B. Qualifying Contest time limit per test 1 second memory limit per test 256 megabytes input standard input output standard output Very soon Berland will hold a School Team Programming Olympiad. From each of the m Berland regions a team of two…

本节主要用于机器学习入门,介绍两个简单的分类模型: 决策树和随机森林 不涉及内部原理,仅仅介绍基础的调用方法 1. How Models Work 以简单的决策树为例 This step of capturing patterns from data is called fitting or training the model The data used to train the data is called the trainning data After the model has bee…

Awesome Go      financial support to Awesome Go A curated list of awesome Go frameworks, libraries and software. Inspired by awesome-python. Contributing Please take a quick gander at the contribution guidelines first. Thanks to all contributors; you…

Robust and Fast 3D Scan Alignment Using Mutual Information 使用互信息进行稳健快速的三维扫描对准 https://arxiv.org/pdf/1709.06948.pdf Nikhil Mehta, James R. McBride and Gaurav Pandey Abstract—This paper presents a mutual information (MI) based algorithm for the estimat…

B. Qualifying Contest Very soon Berland will hold a School Team Programming Olympiad. From each of the m Berland regions a team of two people is invited to participate in the olympiad. The qualifying contest to form teams was held and it was attended…

转自:https://zhuanlan.zhihu.com/p/79934510 风控业务背景 在风控中,我们常用KS指标来评估模型的区分度(discrimination).这也是风控模型同学最为追求的指标之一.那么,有多少人真正理解KS背后的内涵?本文将从区分度的概念.KS的计算方法.业务指导意义.几何解释.数学思想等多个维度展开分析,以期对KS指标有更为深入的理解认知. 目录Part 1. 直观理解区分度的概念Part 2. KS统计量的定义Part 3. KS的计算过程及业务分析Part…

1.Information publication:EMNLP 2014 author:Jing Liu(在前一篇sigir基础上,拓展模型的论文) 2.What 衡量CQA中问题的困难程度,提出从两个方向建模 1)利用Competition的比较:Competition Modelq = {ua ≺q , q ≺ub , ua ≺ub , uo1 ≺ub , · · · , uoM ≺ub } , 2) question Text Similarities for QDE,相似程度的问题具有相…

Visual Object Tracking based on Adaptive Siamese and Motion Estimation 本文提出一种利用上一帧目标位置坐标,在本帧中找出目标可能出现的位置的网路--motion estimation network (named MEN)  .在产生候选位置时,本文从两个可能的坐标下手,采用高斯分布产生很多候选框.然后将候选框送进Siamese Network进行相似性对比. 作者选用最近几帧的目标作为匹配对象(Buffer),提升鲁棒性.…

基于多重虚拟扩展阵列的宽带信号DOA估计[1]. 宽带DOA估计是阵列信号处理领域的一个重要研究方向.在DOAs估计的实际应用中,信号总是会被噪声破坏,在某些情况下,源信号的数量大于传感器的数量,因此不能通过一些传统的算法正确地解决源问题.文中提出了一种将空间重采样和四阶累积量相结合的宽带DOAs方法——多重虚拟扩展阵列(MVEA).在信源个数大于传感器个数的情况下,MVEA能够正确地找到宽带源的方向,通过空间重采样和四阶累积量的虚拟扩展,MVEA获得了比仅采用空间重采样虚拟扩展(SRVE)的方…

目录 概 主要内容 方法 损失函数的转换 一个例子 Hyv"{a}rinen A. Estimation of Non-Normalized Statistical Models by Score Matching. Journal of Machine Learning Research, 2005. 概 我们常常会建模如下的概率模型: \[p(\xi;\theta) = \frac{1}{Z(\theta)} q(\xi; \theta). \] 比如energy-based models.…