图 书 馆开课单位--卡内基梅隆大学
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31What do You Mean? Interpreting Image Classification with Crowdsourced Concept Extraction and AnalysisTowards a Lightweight, Hybrid Approach for Detecting DOM XSS Vulnerabilities with Machine Learning[基于机器学习的DOM XSS漏洞检测的轻量级混合方法]
Clement Fung(卡内基梅隆大学) Towards a Lightweight, Hybrid Approach for Detecting DOM XSS Vulnerabilities with Machine Learning
热度：24
Clement Fung(卡内基梅隆大学) Towards a Lightweight, Hybrid Approach for Detecting DOM XSS Vulnerabilities with Machine Learning
热度：24
32Where are you taking me? Understanding Abusive Traffic Distribution Systems[你要带我去哪里？了解滥用流量分配系统]
Janos Szurdi(卡内基梅隆大学) Where are you taking me? Understanding Abusive Traffic Distribution Systems
热度：28
Janos Szurdi(卡内基梅隆大学) Where are you taking me? Understanding Abusive Traffic Distribution Systems
热度：28
33Knowledge Embedding Based Graph Convolutional Network[基于知识嵌入的图卷积网络]
Donghan Yu(卡内基梅隆大学) Knowledge Embedding Based Graph Convolutional Network
热度：64
Donghan Yu(卡内基梅隆大学) Knowledge Embedding Based Graph Convolutional Network
热度：64
34Discovering and removing barriers to learning[发现并消除学习障碍]
Kenneth R. Koedinger(卡内基梅隆大学) We have developed analytic methods to discover barriers to student learning from data for educational technology use (see learnlab.org). Such discover...
热度：42
Kenneth R. Koedinger(卡内基梅隆大学) We have developed analytic methods to discover barriers to student learning from data for educational technology use (see learnlab.org). Such discover...
热度：42
35What can machine learning do for open education?[机器学习能为开放教育做些什么？]
Geoffrey J. Gordon(卡内基梅隆大学) One of the big promises of open and massively online education is easy data collection: we can record everything from students’ habits in readin...
热度：54
Geoffrey J. Gordon(卡内基梅隆大学) One of the big promises of open and massively online education is easy data collection: we can record everything from students’ habits in readin...
热度：54
36Massively Multilingual Language Technologies[大规模多语言语言技术]
Jaime Carbonell(卡内基梅隆大学) The so-called "digital divide" addressed the challenge of poorer people not having access to the internet and all the myriad resources that ...
热度：56
Jaime Carbonell(卡内基梅隆大学) The so-called "digital divide" addressed the challenge of poorer people not having access to the internet and all the myriad resources that ...
热度：56
37Connectionist Temporal Classification for End-to-End Speech Recognition[用于端到端语音识别的连接主义时间分类]
Florian Metze(卡内基梅隆大学) The performance of automatic speech recognition (ASR) has improved tremendously due to the application of deep neural networks (DNNs). Despite this pr...
热度：96
Florian Metze(卡内基梅隆大学) The performance of automatic speech recognition (ASR) has improved tremendously due to the application of deep neural networks (DNNs). Despite this pr...
热度：96
38Learning Using Local Membership Queries [使用本地成员资格查询学习]
Pranjal Awasthi(卡内基梅隆大学) We introduce a new model of membership query (MQ) learning, where the learning algorithm is restricted to query points that are close to random exampl...
热度：40
Pranjal Awasthi(卡内基梅隆大学) We introduce a new model of membership query (MQ) learning, where the learning algorithm is restricted to query points that are close to random exampl...
热度：40
39Learning a Predictable and Generative Vector Representation for Objects[学习对象的可预测生成向量表示]
Rohit Girdhar(卡内基梅隆大学) What is a good vector representation of an object? We believe that it should be generative in 3D, in the sense that it can produce new 3D objects; as ...
热度：55
Rohit Girdhar(卡内基梅隆大学) What is a good vector representation of an object? We believe that it should be generative in 3D, in the sense that it can produce new 3D objects; as ...
热度：55
40Adversarial Attacks On ML Systems[对机器学习系统的对抗性攻击]
Bhiksha Raj(卡内基梅隆大学) As neural network classifiers become increasingly successful at various tasks ranging from speech recognition and image classification to various natu...
热度：40
Bhiksha Raj(卡内基梅隆大学) As neural network classifiers become increasingly successful at various tasks ranging from speech recognition and image classification to various natu...
热度：40