图 书 馆开课单位--南加州大学
11
12
13
14
15
16
17
18
19
20
11Semantic Challenges in Getting Work Done[完成工作的语义挑战]
Yolanda Gil(南加州大学) In the new millennium, work involves an increasing amount of tasks that are knowledge-rich and collaborative. We are investigating how semantics can h...
热度：39
Yolanda Gil(南加州大学) In the new millennium, work involves an increasing amount of tasks that are knowledge-rich and collaborative. We are investigating how semantics can h...
热度：39
12Legal Interpretation via Dictionaries and Corpora: Can Judges Pass Lexicography 101?[通过词典和语料库进行法律解释：法官能通过词典编纂101吗？]
Edward Finegan(南加州大学) Appellate court judges in the U.S., including those on the Supreme Court, increasingly cite definitions from general dictionaries in their written opi...
热度：65
Edward Finegan(南加州大学) Appellate court judges in the U.S., including those on the Supreme Court, increasingly cite definitions from general dictionaries in their written opi...
热度：65
13Mind Your Metadata: Exploiting Semantics for Configuration, Adaptation, and Provenance in Scientific Workflows[注意你的元数据：利用语义的配置，适应，和科学的工作流程中的出处]
Pedro Szekely(南加州大学) Scientific metadata containing semantic descriptions of scientific data is expensive to capture and is typically not used across entire data analytic ...
热度：53
Pedro Szekely(南加州大学) Scientific metadata containing semantic descriptions of scientific data is expensive to capture and is typically not used across entire data analytic ...
热度：53
14Online Large-Margin Training of Syntactic and Structural Translation Features[句法结构的翻译功能的在线大幅度培训]
David Chiang(南加州大学) 最小错误率训练（MERT）是在统计机器翻译当前发展的一个瓶颈（机器翻译）因为它难以估计的十几个或两个参数。我将提出，翻译模型在耶罗层次短语中的不足，两类特...
热度：44
David Chiang(南加州大学) 最小错误率训练（MERT）是在统计机器翻译当前发展的一个瓶颈（机器翻译）因为它难以估计的十几个或两个参数。我将提出，翻译模型在耶罗层次短语中的不足，两类特...
热度：44
1516Growing a Tree in the Forest: Constructing Folksonomies by Integrating Structured Metadata[生长在森林的一棵树上：通过整合结构化元数据进行构造分类]
Anon Plangprasopchok(南加州大学) Many social Web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchicall...
热度：41
Anon Plangprasopchok(南加州大学) Many social Web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchicall...
热度：41
17Learning an Outlier-Robust Kalman Filter[学习异常强劲的卡尔曼滤波器]
Jo-Anne Ting(南加州大学) In this talk, we introduce a modified Kalman filter that performs robust, real-time outlier detection, without the need for manual parameter tuning by...
热度：128
Jo-Anne Ting(南加州大学) In this talk, we introduce a modified Kalman filter that performs robust, real-time outlier detection, without the need for manual parameter tuning by...
热度：128
18Parallel Exact Inference on Multi-Core Processors[多核处理器的并行精确推理]
Viktor Prasanna(南加州大学) Exact inference in Bayesian networks is a fundamental AI technique that has numerous applications including medical diagnosis, consumer help desk, pat...
热度：28
Viktor Prasanna(南加州大学) Exact inference in Bayesian networks is a fundamental AI technique that has numerous applications including medical diagnosis, consumer help desk, pat...
热度：28
1924. Narratoria, an Authoring Suite for Digital Interactive Narrative[narratoria，数字交互式叙事创作套件]
Martin van Velsen(南加州大学) The software presented here provides sufficient authoring capabilities to allow users to create training applications using interactive narrative with...
热度：19
Martin van Velsen(南加州大学) The software presented here provides sufficient authoring capabilities to allow users to create training applications using interactive narrative with...
热度：19
20Mining Commonsense Knowledge From Personal Stories in Internet Weblogs[从互联网博客的个人故事中挖掘常识]
Andrew S. Gordon(南加州大学) Recent advances in automated knowledge base construction have created new opportunities to address one of the hardest challenges in Artificial Intelli...
热度：31
Andrew S. Gordon(南加州大学) Recent advances in automated knowledge base construction have created new opportunities to address one of the hardest challenges in Artificial Intelli...
热度：31