Publications
Joint audio-visual mining of uncooperatively collected video: FY14 Line-Supported Information, Computation, and Exploitation Program
Summary
Summary
The rate at which video is being created and gathered is rapidly accelerating as access to means of production and distribution expand. This rate of increase, however, is greatly outpacing the development of content-based tools to help users sift through this unstructured, multimedia data. The need for such technologies becomes...
Bayesian discovery of threat networks
Summary
Summary
A novel unified Bayesian framework for network detection is developed, under which a detection algorithm is derived based on random walks on graphs. The algorithm detects threat networks using partial observations of their activity, and is proved to be optimum in the Neyman-Pearson sense. The algorithm is defined by a...
D4M 2.0 Schema: a general purpose high performance schema for the Accumulo database
Summary
Summary
Non-traditional, relaxed consistency, triple store databases are the backbone of many web companies (e.g., Google Big Table, Amazon Dynamo, and Facebook Cassandra). The Apache Accumulo database is a high performance open source relaxed consistency database that is widely used for government applications. Obtaining the full benefits of Accumulo requires using...
Estimation of Causal Peer Influence Effects
Summary
Summary
The broad adoption of social media has generated interest in leveraging peer influence for inducing desired user behavior. Quantifying the causal effect of peer influence presents technical challenges, however, including how to deal with social interference, complex response functions and network uncertainty. In this paper, we extend potential outcomes to...
Detection theory for graphs
Summary
Summary
Graphs are fast emerging as a common data structure used in many scientific and engineering fields. While a wide variety of techniques exist to analyze graph datasets, practitioners currently lack a signal processing theory akin to that of detection and estimation in the classical setting of vector spaces with Gaussian...
Dynamic Distributed Dimensional Data Model (D4M) database and computation system
Summary
Summary
A crucial element of large web companies is their ability to collect and analyze massive amounts of data. Tuple store databases are a key enabling technology employed by many of these companies (e.g., Google Big Table and Amazon Dynamo). Tuple stores are highly scalable and run on commodity clusters, but...
Discrete optimization using decision-directed learning for distributed networked computing
Summary
Summary
Decision-directed learning (DDL) is an iterative discrete approach to finding a feasible solution for large-scale combinatorial optimization problems. DDL is capable of efficiently formulating a solution to network scheduling problems that involve load limiting device utilization, selecting parallel configurations for software applications and host hardware using a minimum set of...
ITWS microburst prediction algorithm performance, capabilities, and limitations
Summary
Summary
Lincoln Laboratory, under funding from the Federal Aviation Administration (FAA) Terminal Doppler Weather Radar program, has developed algorithms for automatically detecting microbursts. While microburst detection algorithms provide highly reliable warnings of microbursts. there still remains a period of time between microburst onset and pilot reaction during which aircraft are at...