The year 1999 was a standout year for Hollywood movies. Perhaps the imminent threat of Y2K really released people’s creative juices. In that year, we got the Star Wars prequel classic The Phantom ...
Abstract: We study the statistical decision process of detecting the low-rank signal from various signal-plus-noise type data matrices, known as the spiked random matrix models. We first show that the ...
This repository, "frp_rl," implements Free Random Projection for in-context reinforcement learning, allowing agents to adapt seamlessly to new tasks. Explore the core components and algorithms to ...
ABSTRACT: Properties from random matrix theory allow us to uncover naturally embedded signals from different data sets. While there are many parameters that can be changed, including the probability ...
MICSI-RMT is a significant breakthrough as the first market solution designed to enhance the signal-to-noise ratio (SNR) for diffusion and functional MRI. Diffusion MRI involves the exponential signal ...
Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...
Scientists have used random matrix theory to theoretically show that neutrino mass hierarchy can be mathematically explained. Random matrix theory helps explain neutrino mass differences, supporting ...
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