17 citations · 28 across the 5 of their papers we have counts for
6 papers
Barrier Function Overrides For Non-Convex Fixed Wing Flight Control and Self-Driving Cars
Eric Squires, Phillip Odom, Zsolt Kira
Reinforcement Learning (RL) has enabled vast performance improvements for robotics systems. To achieve these results though, the agent often must randomly explore the environment,…
Knowledge-based Refinement of Scientific Publication Knowledge Graphs
Siwen Yan, Phillip Odom, Sriraam Natarajan
We consider the problem of identifying authorship by posing it as a knowledge graph construction and refinement. To this effect, we model this problem as learning a probabilistic l…
User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams
Alexander L. Hayes, Mayukh Das, Phillip Odom +1
One of the key advantages of Inductive Logic Programming systems is the ability of the domain experts to provide background knowledge as modes that allow for efficient search throu…
Multi-class Classification without Multi-class Labels
Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser +2
This work presents a new strategy for multi-class classification that requires no class-specific labels, but instead leverages pairwise similarity between examples, which is a weak…
A probabilistic constrained clustering for transfer learning and image category discovery
Yen-Chang Hsu, Zhaoyang Lv, Joel Schlosser +2
Neural network-based clustering has recently gained popularity, and in particular a constrained clustering formulation has been proposed to perform transfer learning and image cate…
Preference-Guided Planning: An Active Elicitation Approach
Mayukh Das, Phillip Odom, Md. Rakibul Islam +4
Planning with preferences has been employed extensively to quickly generate high-quality plans. However, it may be difficult for the human expert to supply this information without…