44 citations · 81 across the 6 of their papers we have counts for
7 papers
A Statistician Teaches Deep Learning
G. Jogesh Babu, David Banks, Hyunsoon Cho +3
Deep learning (DL) has gained much attention and become increasingly popular in modern data science. Computer scientists led the way in developing deep learning techniques, so the…
Adversarial Risk Analysis (Overview)
David Banks, Víctor Gallego, Roi Naveiro +1
Adversarial risk analysis (ARA) is a relatively new area of research that informs decision-making when facing intelligent opponents and uncertain outcomes. It enables an analyst to…
Bayesian Dynamic Modeling and Monitoring of Network Flows
Xi Chen, David Banks, Mike West
In the context of a motivating study of dynamic network flow data on a large-scale e-commerce web site, we develop Bayesian models for on-line/sequential analysis for monitoring an…
Modeling community structure and topics in dynamic text networks
Teague Henry, David Banks, Christine Chai +1
The last decade has seen great progress in both dynamic network modeling and topic modeling. This paper draws upon both areas to create a Bayesian method that allows topic discover…
Scalable Bayesian modeling, monitoring and analysis of dynamic network flow data
Xi Chen, Kaoru Irie, David Banks +3
Traffic flow count data in networks arise in many applications, such as automobile or aviation transportation, certain directed social network contexts, and Internet studies. Using…
Bayesian Analysis of Dynamic Linear Topic Models
Chris Glynn, Surya T. Tokdar, David L. Banks +1
In dynamic topic modeling, the proportional contribution of a topic to a document depends on the temporal dynamics of that topic's overall prevalence in the corpus. We extend the D…
Data Mining in Electronic Commerce
David L. Banks, Yasmin H. Said
Modern business is rushing toward e-commerce. If the transition is done properly, it enables better management, new services, lower transaction costs and better customer relations.…