O’REILLY、INTEL AI 主办
Put AI to work
2018年4月10-11日:培训
2018年4月11-13日:辅导课 & 会议
北京,中国
Li Erran Li

Li Erran Li
Head of Machine Learning | Adjunct professor, Scale | Columbia University

Website

Li Erran Li is the head of machine learning at Scale and an adjunct professor at Columbia University. Previously, he was chief scientist at Pony.ai. Before that, he was with the perception team at Uber ATG and machine learning platform team at Uber where he worked on deep learning for autonomous driving, led the machine learning platform team technically, and drove strategy for company-wide artificial intelligence initiatives. He started his career at Bell Labs. Li’s current research interests are machine learning, computer vision, learning-based robotics, and their application to autonomous driving. He has a PhD from the computer science department at Cornell University. He’s an IEEE Fellow and an ACM Fellow.

Sessions

09:0012:30 Wednesday, April 11, 2018
Secondary topics:  运输与物流 (Transportation and Logistics)
Li Erran Li (Scale | Columbia University)
尽管最近人工智能等领域取得了很多的进展,但自动驾驶里的主要问题(不管是基础研究还是工程应用上的挑战)离完全被解决还有很大的距离。Erran Li将会探索自动驾驶所用的机器学习的基础,并讨论目前相关工作的进展。 了解更多信息.
09:2009:30 Thursday, April 12, 2018
英文讲话 (Presented in English)
Location: 紫金大厅A(Grand Hall A)
Li Erran Li (Scale | Columbia University)
We have made rapid progress in apply machine learning to solve perception, prediction and planning problems. However, there are fundamental challenges ahead. We need to learn more robust and abstract representations, understand driving scenes, and make decisions in multi-agent settings. 了解更多信息.
11:1511:55 Thursday, April 12, 2018
实施人工智能 (Implementing AI), 模型与方法 (Models and Methods)
Location: 多功能厅3A+B (Function Room 3A+B)
Secondary topics:  增强学习(Reinforcement Learning), 运输与物流 (Transportation and Logistics)
Li Erran Li (Scale | Columbia University)
深度增强学习已经让人工智能体在很多挑战性的领域可以取得超越人类的表现,例如玩Atari的游戏以及下围棋。这一方法还具有能显著地推进自动驾驶的潜力。Erran Li将会讨论近期在模仿学习方面(例如infoGAIL)、策略梯度法和层次增强学习(例如option-critic架构)等方面的进步,以及它们在自动驾驶方面的应用。Erran接着还会介绍在这个领域需要关注的剩余的挑战。 了解更多信息.