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April 10-11, 2018: Training
April 11-13, 2018: Tutorials & Conference
Beijing, CN

Schedule: 传媒、广告、娱乐 (Media, Advertising, Entertainment) sessions

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09:0017:00 Wednesday, April 11, 2018
英文讲话 (Presented in English)
Location: 多功能厅8A+8B(Function Room 8A+8B) Level: Intermediate
Kristian Hammond (Narrative Science)
Even as AI technologies move into common use, many enterprise decision makers remain baffled about what the different technologies actually do and how they can be integrated into their businesses. Rather than focusing on the technologies alone, Kristian Hammond provides a practical framework for understanding your role in problem solving and decision making. Read more.
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10:0510:20 Thursday, April 12, 2018
Location: 紫金大厅A(Grand Hall A)
Hui Xiong (Baidu)
敬请期待更多细节。 Read more.
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11:1511:55 Thursday, April 12, 2018
与人工智能交互 (Interacting with AI)
Location: 报告厅(Auditorium) Level: Intermediate
力周 (Microsoft China)
自2014年5月首次发布以来,超过1亿的来自中国、日本和美国的用户与著名的人工智能产品小冰(Xiaoice)进行了互动,进行了仿人的对话。讲师将会分享过去四年中获得的关键经验教训,并会解释如何使用它们来构建更好的聊天机器人。 Read more.
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13:1013:50 Thursday, April 12, 2018
模型与方法 (Models and Methods), 英文讲话 (Presented in English)
Location: 紫金大厅B(Grand Hall B) Level: Intermediate
Zhefu Shi (University of Missouri)
It is critical to analyze the business impact on finance market from worldwide events. Zhefu Shi explains how to use AI to analyze the impact of financial news, using a financial data pipeline. Zhefu outlines how to extract financial entity information and use it to analyze business impact. All of the components use AI to enhance functionality. Read more.
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14:0014:40 Thursday, April 12, 2018
Danny Lange (Unity Technologies)
Danny Lange demonstrates the role games can play in driving the development of reinforcement learning algorithms. Danny uses the Unity Engine with the ML-Agents toolkit as an example of how dynamic 3D game environments can be utilized for machine learning research. Read more.
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16:2017:00 Friday, April 13, 2018
实施人工智能 (Implementing AI)
Location: 多功能厅5A+B(Function Room 5A+B) Level:
孙玄 (转转公司)
转转的推荐系统从0开始打造,针对业务的不同阶段,一步步发展演进。在发展的过程中经历了全局无个性化推荐阶段、个性化离线推荐阶段、个性化实时推荐阶段、机器学习排序推荐阶段等。 本文会详细讲解不同发展阶段的原因、架构&算法的演进,让同学们对二手交易平台的智能推荐系统能够深刻认识。 Read more.