Deep Learning and Reinforcement Learning

Update: 2016-12-08

Description

In recent years, the growing research on deep learning and reinforcement learning has led to many exciting breakthroughs. However, on the other hand, there are still many open problems regarding deep learning and reinforcement learning. In this session, we will reflect, problem-solve and discuss key missing elements, as well as synthesizing the opportunities for academia and industry to further advance this field.

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In Channel

Hopcroft Interview

2017-08-0901:52

Microsoft Research Asia Research Groups

2017-08-0900:51

Artificial Intelligence Research at Microsoft Research Asia

2017-01-0300:34

Future Talent 2040

2016-12-1401:02:22

MSR AI Engage – Learning and Intelligence

2016-12-0852:07

Machine Learning: Theory Meets Application

2016-12-0801:17:11

Deep Learning and Reinforcement Learning

2016-12-0801:07:21

Social Multimedia and Visual Q&A

2016-12-0857:51

Learning for Vision and Multimedia

2016-12-0801:03:59

Machine Learning System and Infrastructure

2016-12-0801:02:14

Urban Big Data and Urban Computing

2016-12-0801:09:22

3D Real World Capturing and Reconstruction

2016-12-0855:59

Robotics

2016-12-0859:00

Machine Learning: Generative vs. Discriminative

2016-12-0801:00:14

AI and Psychology

2016-12-0848:37

微软计算思维

2016-12-0202:43

Learning at Scale as a Driver of Innovation

2016-11-1546:05

Panel – Engaging with AI: How Human and Machine can Work Together to Shape the Future

2016-11-1544:06

Chasing the Next Big Thing: Why Top Companies are Betting on Research

2016-11-1544:54

A Science of Cyber – Security?

2016-11-1543:43

00:00

Deep Learning and Reinforcement Learning

#box-pro-ellipsis-176142470307870{-webkit-line-clamp:2;}Deep Learning and Reinforcement Learning

Deep Learning and Reinforcement Learning

Microsoft Research Asia

Deep Learning and Reinforcement Learning