Speaker: Stratos Idreos, Harvard University
Speaker: Mohammad Sadoghi, UC Davis
A. Erdem Sarıyüce, University at Buffalo
Abstract: Finding dense substructures in a network is a fundamental graph mining operation, with applications in bioinformatics, social networks, and visualization to name a few. Yet most standard formulations of this problem (like clique, quasi-clique, densest at-least-k subgraph) are NP-hard. Furthermore, the goal is rarely to find the “true optimum” but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine relationships among them. In this talk, I will talk about a framework that we designed to find dense regions of the graph with hierarchical relations.
Panos K. Chrysanthis, University of Pittsburgh
Abstract: Online analytics, in most advanced scientific, business, and defense applications, rely heavily on the efficient execution of large numbers of Aggregate Continuous Queries (ACQs). ACQs continuously aggregate streaming data and periodically produce results such as max or average over a given window of the latest data. It was shown that in processing ACQs it is beneficial to use incremental evaluation, which involves storing and reusing calculations performed over the unchanged parts of the window, rather than performing the re-evaluation of the entire window after each update.
Speaker: Verena Kantere, University of Ottawa
Abstract: Big Data analytics in science and industry are performed on a range of heterogeneous data stores, both traditional and modern, and on a diversity of query engines. Workflows are difficult to design and implement since they span a variety of systems. To reduce development time and processing costs, some automation is needed. In this talk we will present a new platform to manage analytics workflows.
Speaker: Dan Suciu, University of Washington
Speaker: Oliver Kennedy, University at Buffalo
Speaker: Ricardo Jimenez-Peris
Abstract: The talk will present the ultra-scalable distributed algorithm to process transactional management and how it has been implemented as part of the LeanXcale database. The talk will go into the details on how ACID properties have been scaled out independently in a composable manner.
Speaker: Spyros Blanas, The Ohio State University
Speaker: Guoliang Li, Tsinghua University
Abstract: