Publications
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Temporal and multi-source fusion for detection of innovation in collaboration networks
Summary
Summary
A common problem in network analysis is detecting small subgraphs of interest within a large background graph. This includes multi-source fusion scenarios where data from several modalities must be integrated to form the network. This paper presents an application of novel techniques leveraging the signal processing for graphs algorithmic framework...
Planted clique detection below the noise floor using low-rank sparse PCA
Summary
Summary
Detection of clusters and communities in graphs is useful in a wide range of applications. In this paper we investigate the problem of detecting a clique embedded in a random graph. Recent results have demonstrated a sharp detectability threshold for a simple algorithm based on principal component analysis (PCA). Sparse...
Spectral anomaly detection in very large graphs: Models, noise, and computational complexity(92.92 KB)
Summary
Summary
Anomaly detection in massive networks has numerous theoretical and computational challenges, especially as the behavior to be detected becomes small in comparison to the larger network. This presentation focuses on recent results in three key technical areas, specifically geared toward spectral methods for detection.
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...
Sparse matrix partitioning for parallel eigenanalysis of large static and dynamic graphs
Summary
Summary
Numerous applications focus on the analysis of entities and the connections between them, and such data are naturally represented as graphs. In particular, the detection of a small subset of vertices with anomalous coordinated connectivity is of broad interest, for problems such as detecting strange traffic in a computer network...
Spectral subgraph detection with corrupt observations
Summary
Summary
Recent work on signal detection in graph-based data focuses on classical detection when the signal and noise are both in the form of discrete entities and their relationships. In practice, the relationships of interest may not be directly observable, or may be observed through a noisy mechanism. The effects of...
Velocity estimation improvements for the ASR-9 Weather Systems Processor
Summary
Summary
The Airport Surveillance Radar (ASR-9) is a rapid-scanning terminal aircraft detection system deployed at airports around the United States. To provide cost-effective wind shear detection capability at medium-density airports, the Weather Systems Processor (WSP) was developed and added on to the ASR-9 at 35 sites. The WSP on the ASR-9...
A least mean squares approach of iterative array calibration for scalable digital phased array radar panels
Summary
Summary
This paper describes a semiautonomous approach to calibrate a phased array system, with particular use on an S-band aperture that is being developed at MIT Lincoln Laboratory. Each element of the array is controlled by an independent digital phase shifter, whose control signal may be uniquely defined. As active electronically...
A method for improved cross-pol isolation based on the use of auxiliary elements
Summary
Summary
This paper describes a method to answer the following questions: can several of the elements of a phased array be employed as auxiliary (AUX) elements and how can the phase of each be adjusted so that the (1) cross-polarization (cross-pol) isolation is minimized to 40 dB, (2) the sidelobe levels...
Very large graphs for information extraction (VLG) - summary of first-year proof-of-concept study
Summary
Summary
In numerous application domains relevant to the Department of Defense and the Intelligence Community, data of interest take the form of entities and the relationships between them, and these data are commonly represented as graphs. Under the Very Large Graphs for Information Extraction effort--a one-year proof-of-concept study--MIT LL developed novel...