17 citations · 31 across the 5 of their papers we have counts for
9 papers
Discovering Generalizable Skills via Automated Generation of Diverse Tasks
Kuan Fang, Yuke Zhu, Silvio Savarese +1
The learning efficiency and generalization ability of an intelligent agent can be greatly improved by utilizing a useful set of skills. However, the design of robot skills can ofte…
Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations
Zhenyu Jiang, Yifeng Zhu, Maxwell Svetlik +2
Grasp detection in clutter requires the robot to reason about the 3D scene from incomplete and noisy perception. In this work, we draw insight that 3D reconstruction and grasp lear…
Beyond Lexical: A Semantic Retrieval Framework for Textual SearchEngine
Kuan Fang, Long Zhao, Zhan Shen +3
Search engine has become a fundamental component in various web and mobile applications. Retrieving relevant documents from the massive datasets is challenging for a search engine…
Adaptive Procedural Task Generation for Hard-Exploration Problems
Kuan Fang, Yuke Zhu, Silvio Savarese +1
We introduce Adaptive Procedural Task Generation (APT-Gen), an approach to progressively generate a sequence of tasks as curricula to facilitate reinforcement learning in hard-expl…
SERank: Optimize Sequencewise Learning to Rank Using Squeeze-and-Excitation Network
RuiXing Wang, Kuan Fang, RiKang Zhou +2
Learning-to-rank (LTR) is a set of supervised machine learning algorithms that aim at generating optimal ranking order over a list of items. A lot of ranking models have been studi…
KETO: Learning Keypoint Representations for Tool Manipulation
Zengyi Qin, Kuan Fang, Yuke Zhu +2
We aim to develop an algorithm for robots to manipulate novel objects as tools for completing different task goals. An efficient and informative representation would facilitate the…