7 citations · 9 across the 4 of their papers we have counts for
5 papers
Learning to Assemble Novel Structures with Unfamiliar Parts under Semantic Constraints
Jonghyuk Park, Alex Lascarides, Subramanian Ramamoorthy
This paper describes a neurosymbolic architecture for learning to assemble novel structures using evidence from embodied conversations and task demonstrations. We focus on scenario…
Learning Visually Grounded Domain Ontologies via Embodied Conversation and Explanation
Jonghyuk Park, Alex Lascarides, Subramanian Ramamoorthy
In this paper, we offer a learning framework in which the agent's knowledge gaps are overcome through corrective feedback from a teacher whenever the agent explains its (incorrect)…
Interactive Acquisition of Fine-grained Visual Concepts by Exploiting Semantics of Generic Characterizations in Discourse
Jonghyuk Park, Alex Lascarides, Subramanian Ramamoorthy
Interactive Task Learning (ITL) concerns learning about unforeseen domain concepts via natural interactions with human users. The learner faces a number of significant constraints:…
Bootstrapping Distantly Supervised IE using Joint Learning and Small Well-structured Corpora
Lidong Bing, Bhuwan Dhingra, Kathryn Mazaitis +2
We propose a framework to improve performance of distantly-supervised relation extraction, by jointly learning to solve two related tasks: concept-instance extraction and relation…
Active Learning Algorithms for Graphical Model Selection
Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan +1
The problem of learning the structure of a high dimensional graphical model from data has received considerable attention in recent years. In many applications such as sensor netwo…