## Statistics in everyone s backyard an impact study via citation network analysis

In this paper, we take the first step towards understanding the impact statistics has made on other scientific fields in the era of BigData . We use the local clustering technique involving personalized PageRank with conductance for size selection to find the most relevant statistical research area for a given external topic of interest .…

## Deep Reinforcement Learning for Practical Phase Shift Optimization in RIS aided MISO URLLC Systems

Reconfigurable intelligent surfaces (RISs) can assist the wireless systems in providing reliable and low-latency links to realize the requirements inIndustry 4.0.0 . The considered method relies on interacting RIS with industrial scenario by taking actions which are the phase shifts at the RISelements, to maximize the total FBL rate .…

## On the randomness analysis of link quality prediction limitations and benefits

In wireless multi-hop networks, link quality (LQ) is one of the most important metrics and is widely used in higher-layer applications such as routing protocols . Researchers have proposed a lot of link quality prediction models in recent years . However, due to the dynamic and stochastic nature of wirelesstransmission, the performance of the model remains challenging .…

## Verification of MPI programs

In this paper, we outline an approach to verifying parallel programs . A newmathematical model of parallel programs is introduced . The introduced model is illustrated by the verification of the matrix multiplication MPI program .…

## Collaborating with Humans without Human Data

Collaborating with humans requires rapidly adapting to their individual strengths, weaknesses, and preferences . Most standardmulti-agent reinforcement learning techniques produce agents that overfit to their training partners . Alternatively, researchers can collecthuman data, train a human model using behavioral cloning, and then use thatmodel to train “human-aware” agents .…

## Streaming Decision Trees and Forests

Machine learning has successfully leveraged modern data and provided solutions to innumerable real-world problems . Currently, estimators could handle both scenarios with all samples available and situations requiring continuous updates . However, there is still room for improvement on streaming algorithms based onbatch decision trees and random forests, which are the leading methods in batch data tasks .…