10 citations · 17 across the 5 of their papers we have counts for
6 papers
Dynamic Model Predictive Shielding for Provably Safe Reinforcement Learning
Arko Banerjee, Kia Rahmani, Joydeep Biswas +1
Among approaches for provably safe reinforcement learning, Model Predictive Shielding (MPS) has proven effective at complex tasks in continuous, high-dimensional state spaces, by l…
Programming-by-Demonstration for Long-Horizon Robot Tasks
Noah Patton, Kia Rahmani, Meghana Missula +2
The goal of programmatic Learning from Demonstration (LfD) is to learn a policy in a programming language that can be used to control a robot's behavior from a set of user demonstr…
Programmatic Imitation Learning from Unlabeled and Noisy Demonstrations
Jimmy Xin, Linus Zheng, Kia Rahmani +4
Imitation Learning (IL) is a promising paradigm for teaching robots to perform novel tasks using demonstrations. Most existing approaches for IL utilize neural networks (NN), howev…
Multi-modal Program Inference: a Marriage of Pre-trainedLanguage Models and Component-based Synthesis
Kia Rahmani, Mohammad Raza, Sumit Gulwani +5
Multi-modal program synthesis refers to the task of synthesizing programs (code) from their specification given in different forms, such as a combination of natural language and ex…
Repairing Serializability Bugs in Distributed Database Programs via Automated Schema Refactoring
Kia Rahmani, Kartik Nagar, Benjamin Delaware +1
Serializability is a well-understood concurrency control mechanism that eases reasoning about highly-concurrent database programs. Unfortunately, enforcing serializability has a hi…
CLOTHO: Directed Test Generation for Weakly Consistent Database Systems
Kia Rahmani, Kartik Nagar, Benjamin Delaware +1
Relational database applications are notoriously difficult to test and debug. Concurrent execution of database transactions may violate complex structural invariants that constrain…