55 citations · 122 across the 8 of their papers we have counts for
3 papers · 1 filter
Expanding Small-Scale Datasets with Guided Imagination
Yifan Zhang, Daquan Zhou, Bryan Hooi +2
The power of DNNs relies heavily on the quantity and quality of training data. However, collecting and annotating data on a large scale is often expensive and time-consuming. To ad…
Reachability-Aware Laplacian Representation in Reinforcement Learning
Kaixin Wang, Kuangqi Zhou, Jiashi Feng +2
In Reinforcement Learning (RL), Laplacian Representation (LapRep) is a task-agnostic state representation that encodes the geometry of the environment. A desirable property of LapR…
The Geometry of Robust Value Functions
Kaixin Wang, Navdeep Kumar, Kuangqi Zhou +3
The space of value functions is a fundamental concept in reinforcement learning. Characterizing its geometric properties may provide insights for optimization and representation. E…