To bridge the domain gap to real imagery with no labeling, we train another matting network guided by the first network and by a discriminator that judges the quality of composites.
CT scans are promising in providing accurate, fast, and cheap screening and testing of COVID-19.
We propose a new family of policy gradient methods for reinforcement learning, which alternate between sampling data through interaction with the environment, and optimizing a "surrogate" objective function using stochastic gradient ascent.
We propose a conceptually simple and lightweight framework for deep reinforcement learning that uses asynchronous gradient descent for optimization of deep neural network controllers.
#4 best model for Atari Games on Atari 2600 Road Runner
Deep Reinforcement Learning has yielded proficient controllers for complex tasks.