José P. González-BrenesCarnegie Mellon University关注立即认领分享关注立即认领分享基本信息浏览量:23职业迁徙个人简介暂无内容研究兴趣论文共 32 篇作者统计合作学者相似作者按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选时间引用量主题期刊级别合作者合作机构Beyond Word Embeddings: Dense Representations for Multi-Modal DataLuis Armona,José P. González-Brenes, Ralph Edezhaththe florida ai research society(2019)引用23浏览0EI引用230Inferring Course Enrollment from Partial DataJosé P. González-Brenes, Ralph EdezhathAIED(2018)引用23浏览0EI引用230Joint Discovery of Skill Prerequisite Graphs and Student ModelsYetian Chen,José P. González-Brenes,Jin TianEDM(2016)引用30浏览0EI引用300A Data-Driven Approach for Inferring Student Proficiency from Game Activity LogsMohammad Hassan Falakmasir,José P. González-Brenes,Geoffrey J. Gordon,Kristen E. DiCerboL@S(2016)引用13浏览0EI引用130The FAST toolkit for Unsupervised Learning of HMMs with FeaturesYun Huang,Jose Gonzalezbrenes,Peter Brusilovskymag(2015)引用24浏览0引用240Modeling Skill Acquisition Over Time with Sequence and Topic ModelingJosé P. González-BrenesJMLR Workshop and Conference Proceedings(2015)引用32浏览0EI引用320Student modeling applications, recent developments & toolkits [SMART tutorial]José P. González-Brenes,Michael Yudelson,Kai Min Chang,Yoav Bergner,Yun Huangeducational data mining(2015)引用0浏览0引用00Using Data from Real and Simulated Learners to Evaluate Adaptive Tutoring SystemsJosé P. González-Brenes,Yun HuangAIED Workshops(2015)引用27浏览0EI引用270Challenges Of Using Observational Data To Determine The Importance Of Example UsageYun Huang,José P. González-Brenes,Peter BrusilovskyARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015(2015)引用5浏览0EI引用50Your model is predictive— but is it useful? Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring EvaluationJose Gonzalezbrenes,Yun HuangEDM(2015)引用42浏览0EI引用420加载更多作者统计合作学者合作机构D-Core合作者学生导师暂无相似学者,你可以通过学者研究领域进行搜索筛选数据免责声明页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn