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10/07/2022
FedPC: Federated Learning for Language Generation with Personal and Context Preference Embeddings
Federated learning is a training paradigm that learns from multiple dist...
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06/21/2022
Multi-UAV Planning for Cooperative Wildfire Coverage and Tracking with Quality-of-Service Guarantees
In recent years, teams of robot and Unmanned Aerial Vehicles (UAVs) have...
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02/04/2022
Learning Interpretable, High-Performing Policies for Continuous Control Problems
Gradient-based approaches in reinforcement learning (RL) have achieved t...
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02/12/2021
Multimodal Punctuation Prediction with Contextual Dropout
Automatic speech recognition (ASR) is widely used in consumer electronic...
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01/18/2021
Interpretable Policy Specification and Synthesis through Natural Language and RL
Policy specification is a process by which a human can initialize a robo...
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12/03/2020
Using Cross-Loss Influence Functions to Explain Deep Network Representations
As machine learning is increasingly deployed in the real world, it is ev...
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06/14/2019
Personalized Apprenticeship Learning from Heterogeneous Decision-Makers
Human domain experts solve difficult planning problems by drawing on yea...
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03/16/2019
Safe Coordination of Human-Robot Firefighting Teams
Wildfires are destructive and inflict massive, irreversible harm to vict...
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02/15/2019
ProLoNets: Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning
Deep reinforcement learning has seen great success across a breadth of t...
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01/02/2019
Action2Vec: A Crossmodal Embedding Approach to Action Learning
We describe a novel cross-modal embedding space for actions, named Actio...
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04/17/2018