4 papers
Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy
Cameron Allen, Aaron Kirtland, Ruo Yu Tao +7
Reinforcement learning algorithms typically rely on the assumption that the environment dynamics and value function can be expressed in terms of a Markovian state representation. H…
An Unstructured Mesh Approach to Nonlinear Noise Reduction for Coupled Systems
Aaron Kirtland, Jonah Botvinick-Greenhouse, Marianne DeBrito +5
To address noise inherent in electronic data acquisition systems and real world sources, Araki et al. [Physica D: Nonlinear Phenomena, 417 (2021) 132819] demonstrated a grid based…
The Polynomial Learning With Errors Problem and the Smearing Condition
Liljana Babinkostova, Ariana Chin, Aaron Kirtland +2
As quantum computing advances rapidly, guaranteeing the security of cryptographic protocols resistant to quantum attacks is paramount. Some leading candidate cryptosystems use the…
The Ring Learning With Errors Problem: Spectral Distortion
L. Babinkostova, Ariana Chin, Aaron Kirtland +2
We answer a question posed by Y. Elias et al. in [8] about possible spectral distortions of algebraic numbers. We provide a closed form for the spectral distortion of certain class…