Diane Staheli's research while affiliated with Massachusetts Institute of Technology and other places

... However, our ATC algorithm differs from a typical triangle counting algorithm. In recent years, we have witnessed a surge of new triangle counting algorithms due to the HPEC GraphChallenge [39]. We also observed exciting efforts such as matrix multiplication-based triangle counting [40], new loadbalancing mechanisms [41], [42], and subgraph matchingbased triangle counting [43]. ...

... There were in total 14 review papers; some of them also presented theoretical or implementation proposals for further development of SA within SOC environments ( Ahmad et al., 2019 ;Andrade and Yoo, 2019 ;Brynielsson et al., 2016 ;Schuster, 2014 , 2016 ;Debatty and Mees, 2019 ;Franke and Brynielsson, 2014 ;Gomez et al., 2019 ;Gutzwiller et al., 2020 ;Hall et al., 2015 ;McNeese and Hall, 2017 ;Nazir and Han, 2022 ;Pahi et al., 2017 ). The reviews ranged in content from specifically addressing the current state of the art of SA within cybersecurity ( Franke and Brynielsson, 2014 ;Gutzwiller et al., 2020 ), to broader reviews concluding with the proposition of a model of cognitive processes within cyber security ( Andrade and Yoo, 2019 ). ...

... Security awareness in cyber security domain can be described as the attainment of current knowledge and prediction of future knowledge about computer networks, missions and threats over neutral, friendly, and adversary forces [1]. The development of situation awareness (SA) has been demonstrated to be helpful in the cyber security domain to specify, analyze, evaluate, and predict human performance in the cyber attack incidents [2], which is especially crucial in real-time changing situations, where decision-making capacity is paramount to solving security tasks. ...

... We follow an iterative approach in developing the guideline. In the first phase, two undergraduate students (who are co-authors of this paper) investigated the 2017 VAST Challenge Mini-Challenge 1 [30] following the pre-registration practice of articulating their analysis questions and hypotheses while minimizing their exposure to the raw data. Similar to the process of coding in qualitative studies [16], the two students examined the VAST Challenge independently and met over multiple sessions to achieve internal agreement between their listed analysis questions, as well as their overall analysis approach. ...

... Due to the widely-recognized importance across various domains, a number of datasets and benchmarks have been developed for network and graph research, including graph data collections [19][20][21], graph learning [22][23][24][25][26][27][28], and diffusion model [29][30][31] (see Section 2 for details). However, none of them provides a comprehensive benchmark suite for flow problems on graphs. ...

... Stochastic block partitioning (SBP) [6], [8] is a community detection algorithm based on stochastic blockmodel inference. It is of interest to the research community due to its high accuracy, even when the graph community structure is complicated by highly varied community sizes, varied degree distributions within communities, and a high degree of inter-community connectivity, as can be seen by comparing the results obtained on the IEEE/Amazon/MIT Graph Challenge [9]. However, SBP is slower than competing community detection algorithms based on other heuristics, and difficult to parallelize owing to the fact that it is based on an inherently sequential Markov chain Monte Carlo algorithm [9]. ...

... analytics. Introducing important AI problems to the public allows for increased collaboration among diverse research teams and maximization of potential solutions (see Figure 1). Challenges such as YOHO (J.P. Campbell, 1995), MNIST (C.C.Y. LeCun and C.J. Burges, 2017), HPC Challenge (HPC Challenge, 2017), Graph Challenge (E. J. Kepner et al., 2019;S. Samsi et al., 2017), ImageNet (O. Russakovsky et al., 2015) and VAST (K.A. Cook et al., 2014;J Scholtz et al., 2012) have driven major developments in various fields. Each of these challenges have catalyzed critical research efforts in their respective fields: YOHO enabled speech research; MNIST remains foundational to the computer vision research communit ...

... In addition to graph algorithms, some authors [23,34,35] introduced streaming algorithms [36] designed for partitioning dynamic graphs. Generally, dynamic graphs [36] are subject to frequent CRUD operations over the set of vertices and edges. ...

... We compare our algorithm against the two latest champions of the Static Graph Challenge [4]. HavoqGT [28] uses a vertex-centric approach. ...

... Similarly to Monroe et al. [5], we utilize action classes for creating simpler views. Another example of using action classes can be given based on the IEEE VAST Challenge 2015 story [65], in which visitors of an amusement park attended attractions grouped in 12 classes, such as "thrill rides", "shopping", "food", etc. ...