Discrete Logarithm
The discrete logarithm problem, central to cryptography and various computational tasks, focuses on efficiently finding the exponent in an exponentiation operation within a finite group. Current research emphasizes improving algorithms for computing discrete logarithms, particularly within the context of specific applications like machine learning and signal processing, often employing logarithmic transformations to enhance efficiency or numerical stability. These advancements have implications for improving the security of cryptographic systems and optimizing performance in diverse fields, including image processing, speech recognition, and probabilistic reasoning.
Papers
Slaves to the Law of Large Numbers: An Asymptotic Equipartition Property for Perplexity in Generative Language Models
Raghu Mudumbai, Tyler Bell
On Hardware-efficient Inference in Probabilistic Circuits
Lingyun Yao, Martin Trapp, Jelin Leslin, Gaurav Singh, Peng Zhang, Karthekeyan Periasamy, Martin Andraud