4 papers
HashEncoding: Autoencoding with Multiscale Coordinate Hashing
Lukas Zhornyak, Zhengjie Xu, Haoran Tang +1
We present HashEncoding, a novel autoencoding architecture that leverages a non-parametric multiscale coordinate hash function to facilitate a per-pixel decoder without convolution…
Shuffle Augmentation of Features from Unlabeled Data for Unsupervised Domain Adaptation
Changwei Xu, Jianfei Yang, Haoran Tang +3
Unsupervised Domain Adaptation (UDA), a branch of transfer learning where labels for target samples are unavailable, has been widely researched and developed in recent years with t…
Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?
Ofir Nachum, Haoran Tang, Xingyu Lu +3
Hierarchical reinforcement learning has demonstrated significant success at solving difficult reinforcement learning (RL) tasks. Previous works have motivated the use of hierarchy…
Modular Architecture for StarCraft II with Deep Reinforcement Learning
Dennis Lee, Haoran Tang, Jeffrey O Zhang +3
We present a novel modular architecture for StarCraft II AI. The architecture splits responsibilities between multiple modules that each control one aspect of the game, such as bui…