Neural Architecture Search with Reinforcement Learning
Neural networks are powerful and versatile models that solve many complex tasks in areas of image analysis, speech recognition and synthesis, etc. The problem of picking the correct architecture is still generally unsolved and is often done manually.
At the seminar, we will discuss two papers that describe methods that utilize reinforcement learning algorithms to to generate descriptions for neural networks. These methods allow generation of neural networks that surpass other state-of-the-art architectures.
Speaker: Aleksandra Malysheva.
Presentation language: Russian.
Date and Time: March 12th, 20:00-21:30.
Place: Times, room 204.
Videos from previous seminars are available at http://bit.ly/MLJBSeminars
6 April 2020Agent57: Outperforming the Atari Human Benchmark
23 March 2020Dream To Control
16 March 2020Почему иерархическое обучение (иногда) работает?
2 March 2020Model Based RL для игр Atari
17 February 2020A Survey and Critique of Multiagent Deep Reinforcement Learning