Search Results for author: Michael Noseworthy

Found 10 papers, 3 papers with code

Structured Latent Variable Models for Articulated Object Interaction

no code implementations26 May 2023 Emily Liu, Michael Noseworthy, Nicholas Roy

In this paper, we investigate a scenario in which a robot learns a low-dimensional representation of a door given a video of the door opening or closing.

Object

Active Learning of Abstract Plan Feasibility

no code implementations1 Jul 2021 Michael Noseworthy, Caris Moses, Isaiah Brand, Sebastian Castro, Leslie Kaelbling, Tomás Lozano-Pérez, Nicholas Roy

Long horizon sequential manipulation tasks are effectively addressed hierarchically: at a high level of abstraction the planner searches over abstract action sequences, and when a plan is found, lower level motion plans are generated.

Active Learning

Leveraging Past References for Robust Language Grounding

no code implementations CONLL 2019 Subhro Roy, Michael Noseworthy, Rohan Paul, Daehyung Park, Nicholas Roy

We therefore reframe the grounding problem from the perspective of coreference detection and propose a neural network that detects when two expressions are referring to the same object.

Object Referring Expression +1

Predicting Success in Goal-Driven Human-Human Dialogues

no code implementations WS 2017 Michael Noseworthy, Jackie Chi Kit Cheung, Joelle Pineau

We then propose a turn-based hierarchical neural network model that can be used to predict success without requiring a structured goal definition.

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