Paper accepted in PVLDB 2020: Dynamic Parameter Allocation in Parameter Servers

The paper "Dynamic Parameter Allocation in Parameter Servers" by Alexander Renz-Wieland, Rainer Gemulla, Steffen Zeuch and Volker Markl has been accepted at the 2020 Proceedings of the VLDB Endowment (PVLDB). Abstract: To keep up with increasing dataset sizes and model complexity, distributed ...

4 DWS Papers Accepted for ACL 2020!

Four papers by DWS members have been accepted for ACL 2020, the most prestigious conference in natural language processing (NLP).

Paper accepted at ICLR 2020: You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings

The paper "You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings" by Daniel Ruffinelli, Samuel Broscheit and Rainer Gemulla has been accepted at the 2020 International Conference of Learning Representations (ICLR). Abstract: Knowledge graph embedding (KGE) models learn ...

LibKGE knowledge graph embedding library released

LibKGE is a PyTorch-based library for efficient training, evaluation, and hyperparameter optimization of knowledge graph embeddings (KGE). It is highly configurable, easy to use, and extensible.

OPIEC open information extraction corpus & accompanying AKBC 2019 paper released

We have released the OPIEC open information extraction corpus; its accompanying article „OPIEC: An Open Information Extraction Corpus“ by Kiril Gashteovski, Sebastian Wanner, Sven Hertling, Samuel Broscheit, and Rainer Gemulla has been accepted for publication at Automated Knowledge Base ...

Two Papers Accepted for IJCAI 2019

The Papers "Anytime Bottom-Up Rule Learning for Knowledge Graph Completion" by Christian Meilicke, Melisachew Wudage Chekol, Daniel Ruffinelli and Heiner Stuckenschmidt and "PRoFET: Predicting the Risk of Firms from Event Transcripts" by Christoph Kilian Theil, Samuel Broscheit and Heiner ...

Article accepted at ACM TODS: A Unified Framework for Frequent Sequence Mining with Subsequence Constraints

The article „A Unified Framework for Frequent Sequence Mining with Subsequence Constraints“ by Kaustubh Beedkar, Rainer Gemulla und Wim Martens has been accepted for publication in ACM Transactions on Database Systems (TODS). Abstract: Frequent sequence mining methods often make use of constraints ...

Paper accepted at ICDE 2019: Scalable Frequent Sequence Mining With Flexible Subsequence Constraints

The paper „Scalable Frequent Sequence Mining With Flexible Subsequence Constraints“ by Alexander Renz-Wieland, Matthias Bertsch, and Rainer Gemulla has been accepted at the 2019 IEEE International Conference on Data Engineering (ICDE). Abstract: We study scalable algorithms for frequent sequence ...

Data Science Conference LWDA 2018 in Mannheim

The Data and Web Science Group is hosting the Data Science Conference LWDA 2018 in Mannheim on August 22-24, 2018. LWDA, which expands to „Lernen, Wissen, Daten, Analysen“ („Learning, Knowledge, Data, Analytics“), covers recent research in areas such as knowledge discovery, machine learning & data ...

Foto: Anna Logue
Paper accepted at ISWC 2018: Fine-grained Evaluation of Rule- and Embedding-based Systems for Knowledge Graph Completion

The paper "Fine-grained Evaluation of Rule- and Embedding-based Systems for Knowledge Graph Completion" by Christian Meilicke, Manuel Fink, Yanjie Wang, Daniel Ruffinelli, Rainer Gemulla, and Heiner Stuckenschmidt has been accepted at the 2018 International Semantic Web Conference (ISWC). Abstract: ...