Andrew Silva

According to our database, Andrew Silva authored at least 26 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Towards Balancing Preference and Performance through Adaptive Personalized Explainability.

Andrew Silva, Pradyumna Tambwekar, Mariah Schrum, Matthew C. Gombolay

Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024

2023

Natural Language Specification of Reinforcement Learning Policies Through Differentiable Decision Trees.

Pradyumna Tambwekar, Andrew Silva, Nakul Gopalan, Matthew C. Gombolay

IEEE Robotics Autom. Lett., June, 2023

Explainable Artificial Intelligence: Evaluating the Objective and Subjective Impacts of xAI on Human-Agent Interaction.

Andrew Silva, Mariah Schrum, Erin Hedlund-Botti, Nakul Gopalan, Matthew C. Gombolay

Int. J. Hum. Comput. Interact., April, 2023

Interpretable Reinforcement Learning for Robotics and Continuous Control.

Rohan R. Paleja, Letian Chen, Yaru Niu, Andrew Silva, Zhaoxin Li, Songan Zhang, Chace Ritchie, Sugju Choi, Kimberlee Chestnut Chang, Hongtei Eric Tseng, Yan Wang, Subramanya Nageshrao, Matthew C. Gombolay

CoRR, 2023

FedPerC: Federated Learning for Language Generation with Personal and Context Preference Embeddings.

Andrew Silva, Pradyumna Tambwekar, Matthew C. Gombolay

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

2022

LanCon-Learn: Learning With Language to Enable Generalization in Multi-Task Manipulation.

Andrew Silva, Nina Moorman, William Silva, Zulfiqar Zaidi, Nakul Gopalan, Matthew C. Gombolay

IEEE Robotics Autom. Lett., 2022

FedPC: Federated Learning for Language Generation with Personal and Context Preference Embeddings.

Andrew Silva, Pradyumna Tambwekar, Matthew C. Gombolay

CoRR, 2022

FedEmbed: Personalized Private Federated Learning.

Andrew Silva, Katherine Metcalf, Nicholas Apostoloff, Barry-John Theobald

CoRR, 2022

Learning Interpretable, High-Performing Policies for Continuous Control Problems.

Rohan R. Paleja, Yaru Niu, Andrew Silva, Chace Ritchie, Sugju Choi, Matthew C. Gombolay

CoRR, 2022

Multi-UAV planning for cooperative wildfire coverage and tracking with quality-of-service guarantees.

Esmaeil Seraj, Andrew Silva, Matthew C. Gombolay

Auton. Agents Multi Agent Syst., 2022

Learning Interpretable, High-Performing Policies for Autonomous Driving.

Rohan R. Paleja, Yaru Niu, Andrew Silva, Chace Ritchie, Sugju Choi, Matthew C. Gombolay

Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Cross-Loss Influence Functions to Explain Deep Network Representations.

Andrew Silva, Rohit Chopra, Matthew C. Gombolay

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Interpretable Policy Specification and Synthesis through Natural Language and RL.

Pradyumna Tambwekar, Andrew Silva, Nakul Gopalan, Matthew C. Gombolay

CoRR, 2021

Towards a Comprehensive Understanding and Accurate Evaluation of Societal Biases in Pre-Trained Transformers.

Andrew Silva, Pradyumna Tambwekar, Matthew C. Gombolay

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Multimodal Punctuation Prediction with Contextual Dropout.

Andrew Silva, Barry-John Theobald, Nicholas Apostoloff

Proceedings of the IEEE International Conference on Acoustics, 2021

Encoding Human Domain Knowledge to Warm Start Reinforcement Learning.

Andrew Silva, Matthew C. Gombolay

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Using Cross-Loss Influence Functions to Explain Deep Network Representations.

Andrew Silva, Rohit Chopra, Matthew C. Gombolay

CoRR, 2020

Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User Demonstrations.

Rohan R. Paleja, Andrew Silva, Letian Chen, Matthew C. Gombolay

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning.

Andrew Silva, Matthew C. Gombolay, Taylor W. Killian, Ivan Dario Jimenez Jimenez, Sung-Hyun Son

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Personalized Apprenticeship Learning from Heterogeneous Decision-Makers.

Rohan R. Paleja, Andrew Silva, Matthew C. Gombolay

CoRR, 2019

Safe Coordination of Human-Robot Firefighting Teams.

Esmaeil Seraj, Andrew Silva, Matthew C. Gombolay

CoRR, 2019

ProLoNets: Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning.

Andrew Silva, Matthew C. Gombolay

CoRR, 2019

Action2Vec: A Crossmodal Embedding Approach to Action Learning.

Meera Hahn, Andrew Silva, James M. Rehg

CoRR, 2019

Unsupervised Role Discovery Using Temporal Observations of Agents.

Andrew Silva, Sonia Chernova

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Effects of Interruptibility-Aware Robot Behavior.

Siddhartha Banerjee, Andrew Silva, Karen M. Feigh, Sonia Chernova

CoRR, 2018

2005

Analysis of Nonlinear Input Impedance Matching in Active Frequency Multipliers.

Jessi E. Johnson, Andrew Silva, George R. Branner

IEICE Trans. Inf. Syst., 2005