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The current flood of information in all areas of machine learning research, from computer vision to reinforcement learning, has made it difficult to make aggregate scientific inferences. It can be challenging to distill a myriad of similar…
In this paper we describe our experience in developing curriculum courses aimed at graduate students in emerging computational fields, including biology and medical science. We focus primarily on computational data analysis and statistical…
Several authors, including the American Statistician (ASA), have noted the challenges facing statisticians when attacking large, complex, unstructured problems, as opposed to well-defined textbook problems. Clearly, the standard paradigm of…
Matching, capturing allocation of items to unit-demand buyers, or tasks to workers, or pairs of collaborators, is a central problem in economics. Indeed, the growing prevalence of matching-based markets, many of which online in nature, has…
Developments in data visualization research have enabled visualization systems to achieve great general usability and application across a variety of domains. These advancements have improved not only people's understanding of data, but…
Learning analytics (LA) is argued to be able to improve learning outcomes, learner support and teaching. However, despite an increasingly expanding amount of student (digital) data accessible from various online education and learning…
A main driver behind the digitization of industry and society is the belief that data-driven model building and decision making can contribute to higher degrees of automation and more informed decisions. Building such models from data often…
Process analytics approaches allow organizations to support the practice of Business Process Management and continuous improvement by leveraging all process-related data to extract knowledge, improve process performance and support…
Software architecture is the foundation of a system's ability to achieve various quality attributes, including software performance. However, there lacks comprehensive and in-depth understanding of why and how software architecture and…
Edge technology aims to bring Cloud resources (specifically, the compute, storage, and network) to the closed proximity of the Edge devices, i.e., smart devices where the data are produced and consumed. Embedding computing and application…
Network-based marketing refers to a collection of marketing techniques that take advantage of links between consumers to increase sales. We concentrate on the consumer networks formed using direct interactions (e.g., communications) between…
Classification, a heavily-studied data-driven machine learning task, drives an increasing number of prediction systems involving critical human decisions such as loan approval and criminal risk assessment. However, classifiers often…
Analytical information needs, such as trend analysis and causal impact assessment, are prevalent across various domains including law, finance, science, and much more. However, existing information retrieval paradigms, whether based on…
The relevance and importance of contextualizing data analytics is described. Qualitative characteristics might form the context of quantitative analysis. Topics that are at issue include: contrast, baselining, secondary data sources,…
The recent advances in information and communication technology (ICT) have promoted the evolution of conventional computer-aided manufacturing industry to smart data-driven manufacturing. Data analytics in massive manufacturing data can…
Measurement system analysis aims to quantify the variability in data attributable to the measurement system and evaluate its contribution to overall data variability. This paper conducts a rigorous theoretical investigation of the…
This special volume of Statistical Sciences presents some innovative, if not provocative, ideas in the area of reliability, or perhaps more appropriately named, integrated system assessment. In this age of exponential growth in science,…
Promotions are commonly used by e-commerce merchants to boost sales. The efficacy of different promotion strategies can help sellers adapt their offering to customer demand in order to survive and thrive. Current approaches to designing…
Due to the surge of spatio-temporal data volume, the popularity of location-based services and applications, and the importance of extracted knowledge from spatio-temporal data to solve a wide range of real-world problems, a plethora of…
This report provides insights into the challenges, emerging topics, and opportunities related to human-data interaction and visual analytics in the AI era. The BigVis 2024 organizing committee conducted a survey among experts in the field.…