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- research-articleMarch 2024
An eigenmodel for dynamic multilayer networks
The Journal of Machine Learning Research (JMLR), Volume 24, Issue 1Article No.: 128, Pages 5830–5898Dynamic multilayer networks frequently represent the structure of multiple co-evolving relations; however, statistical models are not well-developed for this prevalent network type. Here, we propose a new latent space model for dynamic multilayer ...
- research-articleApril 2020
Near-Perfect Recovery in the One-Dimensional Latent Space Model
WWW '20: Proceedings of The Web Conference 2020April 2020, Pages 1932–1942https://doi.org/10.1145/3366423.3380261Suppose a graph G is stochastically created by uniformly sampling vertices along a line segment and connecting each pair of vertices with a probability that is a known decreasing function of their distance. We ask if it is possible to reconstruct the ...
- research-articleMay 2019
Spatial modeling of brain connectivity data via latent distance models with nodes clustering
Statistical Analysis and Data Mining (STADM), Volume 12, Issue 3June 2019, Pages 185–196https://doi.org/10.1002/sam.11412Brain network data—measuring structural interconnections among brain regions of interest—are increasingly collected for multiple individuals. Moreover, recent analyses provide additional information on the brain regions under study. These predictors ...
- research-articleAugust 2017
Learning a Hierarchical Embedding Model for Personalized Product Search
SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information RetrievalAugust 2017, Pages 645–654https://doi.org/10.1145/3077136.3080813Product search is an important part of online shopping. In contrast to many search tasks, the objectives of product search are not confined to retrieving relevant products. Instead, it focuses on finding items that satisfy the needs of individuals and ...
- articleJanuary 2017
Bayesian learning of dynamic multilayer networks
A plethora of networks is being collected in a growing number of fields, including disease transmission, international relations, social interactions, and others. As data streams continue to grow, the complexity associated with these highly ...
- research-articleAugust 2016
Latent Space Model for Road Networks to Predict Time-Varying Traffic
KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data MiningAugust 2016, Pages 1525–1534https://doi.org/10.1145/2939672.2939860Real-time traffic prediction from high-fidelity spatiotemporal traffic sensor datasets is an important problem for intelligent transportation systems and sustainability. However, it is challenging due to the complex topological dependencies and high ...
- articleJanuary 2014
Consistent Latent Position Estimation and Vertex Classification for Random Dot Product Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence (ITPM), Volume 36, Issue 1January 2014, Pages 48–57https://doi.org/10.1109/TPAMI.2013.135In this work, we show that using the eigen-decomposition of the adjacency matrix, we can consistently estimate latent positions for random dot product graphs provided the latent positions are i.i.d. from some distribution. If class labels are observed ...
- articleJanuary 2013
What you see predicts what you get—lightweight agent-based malware detection
Security and Communication Networks (SACN), Volume 6, Issue 1January 2013, Pages 33–48https://doi.org/10.1002/sec.528Because of the always connected nature of mobile devices, as well as the unique interfaces they expose, such as short message service (SMS), multimedia messaging service (MMS), and Bluetooth, classes of mobile malware tend to propagate using means ...
- articleAugust 2012
Review of statistical network analysis: models, algorithms, and software
Statistical Analysis and Data Mining (STADM), Volume 5, Issue 4August 2012, Pages 243–264https://doi.org/10.1002/sam.11146The analysis of network data is an area that is rapidly growing, both within and outside of the discipline of statistics.
This review provides a concise summary of methods and models used in the statistical analysis of network data, including the Erdős–...