FitMine: automatic mining for time-evolving signals of cardiotocography monitoring
The monitoring and assessment of the fetus condition are considered to be among the most important obstetric issues to consider during pregnancy and the prenatal period. Monitoring the fetal condition is required to detect the presence of any ...
Retrieving geometric information from images: the case of hand-drawn diagrams
This paper addresses the problem of retrieving meaningful geometric information implied in image data. We outline a general algorithmic scheme to solve the problem in any geometric domain. The scheme, which depends on the domain, may lead to concrete ...
Scalable density-based clustering with quality guarantees using random projections
Clustering offers significant insights in data analysis. Density-based algorithms have emerged as flexible and efficient techniques, able to discover high-quality and potentially irregularly shaped clusters. Here, we present scalable density-based ...
Discrimination of Alzheimer's Disease using longitudinal information
Alzheimer's Disease (AD) is a neurological disorder that leads to a loss of cognitive functioning, affecting older people as well as their families. Although a few treatments are available to slow down the progress of the disease, they are limited in ...
Enhancing social collaborative filtering through the application of non-negative matrix factorization and exponential random graph models
Social collaborative filtering recommender systems extend the traditional user-to-item interaction with explicit user-to-user relationships, thereby allowing for a wider exploration of correlations among users and items, that potentially lead to better ...
Measuring discrimination in algorithmic decision making
Society is increasingly relying on data-driven predictive models for automated decision making. This is not by design, but due to the nature and noisiness of observational data, such models may systematically disadvantage people belonging to certain ...
The PRIMPING routine--Tiling through proximal alternating linearized minimization
Mining and exploring databases should provide users with knowledge and new insights. Tiles of data strive to unveil true underlying structure and distinguish valuable information from various kinds of noise. We propose a novel Boolean matrix ...
Robust unsupervised cluster matching for network data
Unsupervised cluster matching is a task to find matching between clusters of objects in different domains. Examples include matching word clusters in different languages without dictionaries or parallel sentences and matching user communities across ...