Recent genome sequencing studies have shown that the somatic mutations that drive
cancer development are distributed across a large number of genes. This mutational …

© 2018 VLDB Endowment. In order to democratize data science, we need to fundamentally
rethink the current analytics stack, from the user interface to the “guts.“Most importantly …

Slice finding---a recent work on debugging machine learning (ML) models---aims to find the
top-K data slices (eg, conjunctions of predicates such as gender female and degree PhD) …

In this paper, we investigate the highly reliable subgraph problem, which arises in the
context of uncertain graphs. This problem attempts to identify all induced subgraphs for …

Mining matrices to find relevant biclusters, subsets of rows exhibiting a coherent pattern over
a subset of columns, is a critical task for a wide-set of biomedical and social applications …

In recent years, there has been significant growth in the use of ontology-based methods to
enhance data interestingness. These methods play a crucial role in knowledge …

Discriminative sequential patterns are sub-sequences whose occurrences exhibit significant
differences across sequential data sets with different class labels. The discovery of such …

Statistical evaluation of biclustering solutions is essential to guarantee the absence of
spurious relations and to validate the high number of scientific statements inferred from …

Assessing rules with interestingness measures is the pillar of successful application of
association rules discovery. However, association rules discovered are normally large in …

We are interested in discovering those patterns from data with an empirical frequency that is
significantly differently than expected. To avoid spurious results, yet achieve high statistical …