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09/04/2023
On the Consistency and Robustness of Saliency Explanations for Time Series Classification
Interpretable machine learning and explainable artificial intelligence h...
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07/30/2023
Redundancy-aware unsupervised rankings for collections of gene sets
The biological roles of gene sets are used to group them into collection...
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07/04/2023
Prototypes as Explanation for Time Series Anomaly Detection
Detecting abnormal patterns that deviate from a certain regular repeatin...
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03/24/2023
Interpretable Anomaly Detection via Discrete Optimization
Anomaly detection is essential in many application domains, such as cybe...
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03/14/2023
RODD: Robust Outlier Detection in Data Cubes
Data cubes are multidimensional databases, often built from several sepa...
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05/17/2022
Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data
Not all real-world data are labeled, and when labels are not available, ...
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08/13/2020
Statistical Evaluation of Anomaly Detectors for Sequences
Although precision and recall are standard performance measures for anom...
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06/30/2020
Graph Clustering with Graph Neural Networks
Graph Neural Networks (GNNs) have achieved state-of-the-art results on m...
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06/23/2020
Differentiable Segmentation of Sequences
Segmented models are widely used to describe non-stationary sequential d...
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06/08/2020
FREDE: Linear-Space Anytime Graph Embeddings
Low-dimensional representations, or embeddings, of a graph's nodes facil...
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04/30/2020
Does Terrorism Trigger Online Hate Speech? On the Association of Events and Time Series
Hate speech is ubiquitous on the Web. Recently, the offline causes that ...
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01/31/2020
Two-Sample Testing for Event Impacts in Time Series
In many application domains, time series are monitored to detect extreme...
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06/06/2019
Deep Semi-Supervised Anomaly Detection
Deep approaches to anomaly detection have recently shown promising resul...
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05/27/2019
Intrinsic Multi-scale Evaluation of Generative Models
Generative models are often used to sample high-dimensional data points ...
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11/15/2018
SGR: Self-Supervised Spectral Graph Representation Learning
Representing a graph as a vector is a challenging task; ideally, the rep...
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03/13/2018