Conference paper
Topological Data Analysis on Noisy Quantum Computers
Ismail Akhalwaya, Shashanka Ubaru, et al.
ICLR 2024
In this paper, we introduce a new approach to Programming-by-Demonstration in which the author is allowed to explicitly edit the procedure model produced by the learning algorithm while demonstrating the task. We describe Augmentation-Based Learning, a new algorithm that supports this approach by considering both demonstrations and edits as constraints on the hypothesis space, and resolving conflicts in favor of edits. © 2007 Elsevier B.V. All rights reserved.
Ismail Akhalwaya, Shashanka Ubaru, et al.
ICLR 2024
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