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

用于自动驾驶的机器学习

此演讲使用中文 (This will be presented in Chinese)

Li Erran Li (Scale | Columbia University)
09:0012:30 Wednesday, April 11, 2018
Secondary topics:  运输与物流 (Transportation and Logistics)

必要预备知识 (Prerequisite Knowledge)

有深度学习和增强学习的基本知识

该辅导课要求硬件和/或安装 (Hardware and/or installation requirements)

下载教学辅导课幻灯片(链接请参考本页上部)

您将学到什么 (What you'll learn)

理解用于自动驾驶的机器学习的方法

描述 (Description)

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。


大纲

:


 分解化的方法:

  • 对象检测和分类(例如R-FCN、F-PointNets)


  • 对象跟踪


  • 语义场景理解



规划和控制:模型预测控制(例如iLQR)

  • 一个端到端的方法(从原始的传感器输入到驾驶的命令)

  • 模仿学习:DAGGER、infoGAIL
    *
用于驾驶策略的深度增强学习:自然策略梯度,例如A3C和变化降低


  • 高效地学习*
  • 领域适应和用于感知和行动的迁移学习
  • 无监督学习
Photo of Li Erran Li

Li Erran Li

Scale | Columbia University

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.