Graduate Student, Department of Electrical and Computer Engineering.
Identifying contamination in datasets is important in a wide variety of settings, including view and click fraud in online advertising. After a brief overview of digital ad fraud, I’ll describe a technique for estimating contamination in large, categorical datasets. The technique involves solving a series of convex programs, resulting in …
Digital adverting is arguably the largest and most ubiquitous application of machine learning. Learning algorithms pick the ads we see by inferring information about who we are and what we might buy. Graph datasets, due to their simplicity, play a central role in facilitating this inference. Internet Device Graphs are …
Jagdish Ramakrishnan In radiation therapy, the fractionation schedule, i.e. the total number of treatment days and the dose delivered per day, plays an important role in treatment outcome. In the first part of the talk, we analyze the effect of tumor repopulation on the optimal fractionation scheme. We find that …
Matt’s talk: Title: Sequential Testing in High Dimensions Sequential methods make use of information as it becomes available, creating an interactive connection between a sampling procedure and information gathered by that procedure. In this talk we explore sequential methods applied to sparse recovery problems, motivated by applications in both communications …
This week, we’ll hear belated summaries from three graduate students about their internships over the summer. Each presenter will speak for about 15 minutes. John Brady — NASA Langley Research Center. John worked on testing and modifying a communications protocol for use in the Climate Absolute Radiance and Refractivity Observatory …