Are two sets of data genuinely different, or is it because of randomness? This question, known as the two-sample testing problem, becomes notoriously difficult in modern datasets, because they are ...

Abstract: The amount of information lost in sub-Nyquist sampling of a continuous-time Gaussian stationary process is quantified. We consider a combined source coding and sub-Nyquist reconstruction ...

Reinforcement learning is a framework for interactive decision-making with incentives sequentially revealed across time without a system dynamics model. Due to its scaling to continuous spaces, we ...

Abstract: The energy resolution of ultraviolet photoelectron spectroscopy (UPS) instrument is one of the important parameters for evaluating surface electronic structure. This study systematically ...

2024-5-22: We are pleased to announce that we have submitted NeuroGauss4D-PCI to meeting 2024. We extend our heartfelt thanks to all the reviewers for their valuable feedback. Please follow ...

This research paper was presented at the 17 th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (opens in new tab), a premier forum for advances in the theory ...

This repository contains the source code for the “Thompson sampling efficient multiobjective optimization” (TSEMO) algorithm outlined in (Bradford et al., 2018). The algorithm is written to optimize ...

The link between mind, brain, and behavior has mystified philosophers and scientists for millennia. Recent progress has been made by forming statistical associations between manifest variables of the ...