Search Results for author: Steffen Staab

Found 21 papers, 10 papers with code

Ultrahyperbolic Knowledge Graph Embeddings

no code implementations1 Jun 2022 Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chengjin Xu, Shirui Pan, Chuan Zhou, Steffen Staab

Recent knowledge graph (KG) embeddings have been advanced by hyperbolic geometry due to its superior capability for representing hierarchies.

Knowledge Graph Embeddings

Detecting Anomalies within Time Series using Local Neural Transformations

1 code implementation8 Feb 2022 Tim Schneider, Chen Qiu, Marius Kloft, Decky Aspandi Latif, Steffen Staab, Stephan Mandt, Maja Rudolph

We develop a new method to detect anomalies within time series, which is essential in many application domains, reaching from self-driving cars, finance, and marketing to medical diagnosis and epidemiology.

Anomaly Detection Epidemiology +3

Fairness implications of encoding protected categorical attributes

no code implementations27 Jan 2022 Carlos Mougan, Jose M. Alvarez, Gourab K Patro, Salvatore Ruggieri, Steffen Staab

Protected attributes are often presented as categorical features that need to be encoded before feeding them into a machine learning algorithm.

Fairness Feature Engineering

Box Embeddings for the Description Logic EL++

1 code implementation24 Jan 2022 Bo Xiong, Nico Potyka, Trung-Kien Tran, Mojtaba Nayyeri, Steffen Staab

Recently, various methods for representation learning on Knowledge Bases (KBs) have been developed.

Knowledge Graph Embedding

Wikidated 1.0: An Evolving Knowledge Graph Dataset of Wikidata's Revision History

1 code implementation9 Dec 2021 Lukas Schmelzeisen, Corina Dima, Steffen Staab

Wikidata is the largest general-interest knowledge base that is openly available.

ProGS: Property Graph Shapes Language (Extended Version)

1 code implementation12 Jul 2021 Philipp Seifer, Ralf Lämmel, Steffen Staab

In RDF representations, this error can be addressed by shape languages such as SHACL or ShEx, which allow for checking whether graphs are valid with respect to a set of domain constraints.

Knowledge Graphs

Learning Gradual Argumentation Frameworks using Genetic Algorithms

1 code implementation25 Jun 2021 Jonathan Spieler, Nico Potyka, Steffen Staab

As a first proof of concept, we propose a genetic algorithm to simultaneously learn the structure of argumentative classification models.

Interpretable Machine Learning

Semi-Riemannian Graph Convolutional Networks

no code implementations6 Jun 2021 Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, Steffen Staab

As a consequence, we derive a principled Semi-Riemannian GCN that first models data in semi-Riemannian manifolds of constant nonzero curvature in the context of graph neural networks.

Inductive Bias

Hybrid Physics and Deep Learning Model for Interpretable Vehicle State Prediction

no code implementations11 Mar 2021 Alexandra Baier, Zeyd Boukhers, Steffen Staab

Physical motion models offer interpretable predictions for the motion of vehicles.

LaHAR: Latent Human Activity Recognition using LDA

1 code implementation23 Nov 2020 Zeyd Boukhers, Danniene Wete, Steffen Staab

Processing sequential multi-sensor data becomes important in many tasks due to the dramatic increase in the availability of sensors that can acquire sequential data over time.

Human Activity Recognition

MOFA: Modular Factorial Design for Hyperparameter Optimization

no code implementations18 Nov 2020 Bo Xiong, Yimin Huang, Hanrong Ye, Steffen Staab, Zhenguo Li

MOFA pursues several rounds of HPO, where each round alternates between exploration of hyperparameter space by factorial design and exploitation of evaluation results by factorial analysis.

Hyperparameter Optimization Model Selection

Knowledge Graphs

2 code implementations4 Mar 2020 Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d'Amato, Gerard de Melo, Claudio Gutierrez, José Emilio Labra Gayo, Sabrina Kirrane, Sebastian Neumaier, Axel Polleres, Roberto Navigli, Axel-Cyrille Ngonga Ngomo, Sabbir M. Rashid, Anisa Rula, Lukas Schmelzeisen, Juan Sequeda, Steffen Staab, Antoine Zimmermann

In this paper we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data.

Knowledge Graphs

Understanding Social Networks using Transfer Learning

no code implementations16 Oct 2019 Jun Sun, Steffen Staab, Jérôme Kunegis

A detailed understanding of users contributes to the understanding of the Web's evolution, and to the development of Web applications.

Transfer Learning

Observing and Recommending from a Social Web with Biases

no code implementations25 Apr 2016 Steffen Staab, Sophie Stalla-Bourdillon, Laura Carmichael

The research question this report addresses is: how, and to what extent, those directly involved with the design, development and employment of a specific black box algorithm can be certain that it is not unlawfully discriminating (directly and/or indirectly) against particular persons with protected characteristics (e. g. gender, race and ethnicity)?

A Generalized Language Model as the Combination of Skipped n-grams and Modified Kneser-Ney Smoothing

1 code implementation13 Apr 2014 Rene Pickhardt, Thomas Gottron, Martin Körner, Paul Georg Wagner, Till Speicher, Steffen Staab

In an extensive empirical experiment over English text corpora we demonstrate that our generalized language models lead to a substantial reduction of perplexity between 3. 1% and 12. 7% in comparison to traditional language models using modified Kneser-Ney smoothing.

Language Modelling

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