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Prof. Dr. Philipp Kellmeyer
Prof. Dr. Han van der Aa
Prof. Dr. Paul Swoboda
Prof. Dr. Christian Bizer
Prof. Dr. Rainer Gemulla
Prof. Dr. Simone Paolo Ponzetto
Prof. Dr. Heiko Paulheim
Prof. Dr. Heiner Stuckenschmidt
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Dr. Ines Rehbein
Dr. Ioana Hulpus
Dr. Melisachew Wudage Chekol
Dr. Christian Meilicke
Dr. Pedro Ortiz Suarez
Dr. Federico Nanni
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Darshit Pandya
Sarah Alturki
Alexander Beier
Patrick Betz
Alexander Brinkmann
Samuel Broscheit
Lea Cohausz
Nicolas Heist
Sven Hertling
Chia-Chien Hung
Andreea Iana
Jakob Kappenberger
Christopher Klamm
Adrian Kochsiek
Keti Korini
Franz Krause
Steffen Jung
Amirhossein Kardoost
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Alexander Kraus
Robert Litschko
Jovita Lukasik
Ralph Peeters
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Daniel Ruffinelli
Michael Schlechtinger
Fabian David Schmidt
Sotaro Takeshita
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Prof. Dr. Goran Glavaš
Dr. Anna Primpeli
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Dr. Timo Sztyler
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Dr. Yaser Oulabi
Alexander Diete
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Stefan Morio
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Web-based Systems (Prof. Bizer)
Data Analytics (Prof. Gemulla)
Web Data Mining (Prof. Paulheim)
Natural Language Processing and Information Retrieval (Prof. Ponzetto)
Artificial Intelligence (Prof. Stuckenschmidt)
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Process Analytics (Prof. Van der Aa)
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Courses for Master Candidates
IE 696 Advanced Methods in Text Analytics
IE 500 Data Mining
IE 560 Decision Support
IE 650 Knowledge Graphs
IE 661 Text Analytics
IE 663 Information Retrieval and Web Search
IE 670 Web Data Integration
IE 671 Web Mining
IE 672 Data Mining 2
IE 675b Machine Learning
IE 678 Deep Learning
IE 689 Relational Learning
IE 692 Advanced Process Mining
IE 694 Industrial Applications of Artificial Intelligence
CS 460 Database Technology
CS 560 Large-Scale Data Management
CS 704 Artificial Intelligence Seminar
CS 704 Social Simulation Seminar
CS 704 Seminar on Traffic Simulation & Analysis
CS 709 Text Analytics Seminar
CS 710 Seminar on Knowledge Graph Construction
CS 715: Large-Scale Data Integration Seminar
CS 718 AI and Data Science in Fiction and Society
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University of Mannheim
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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 ...
Paper accepted for DI2KG
The paper “Intermediate Training of BERT for Product Matching” by Ralph Peeters, Christian Bizer and Goran Glavaš has been accepted for the 2nd International Workshop on Challenges and Experiences from Data Integration to Knowledge Graphs (DI2KG) held in conjunction with VLDB 2020.
Paper accepted for CIKM
The paper “Profiling Entity Matching Benchmark Tasks” by Anna Primpeli and Christian Bizer has been accepted for the 29th International Conference on Information and Knowledge Management (CIKM) which will be held online this year.
Two Contributions to the ECML/
PKDD PhD Forum
Christian Schreckenberger and Sascha Marton will present their PhD Topics at the PhD Forum of ECML / PKDD 2020: Christian Schreckenberger, Christian Bartelt and Heiner Stuckenschmidt: Tree-based Learning for Dynamic Data Streams Sascha Marton, Christian Bartelt and Heiner Stuckenschmidt: Machine ...
Two New Projects on Social Impacts of AI Started
As part of a new research program for the common good-oriented handling of artificial intelligence (AI) three projects of the University of Mannheim are funded by the Baden-Württemberg Foundation.
Paper Accepted at International Journal of Production Economics
The paper Intraday Shelf Replenishment Decision Support for perishable Goods by Jakob Huber and Heiner Stuckenschmidt has been accepted by the International Journal of Production Economics (Elsevier, Impact Factor 4,998).
Paper Accepted for International Journal of Forecasting
The paper “Daily Retail Demand Forecasting Using Machine Learning with Emphasis on Calendric Special Days” by Jakob Huber and Heiner Stuckenschmidt has been accepted for the International Journal of Forecasting (Impact Factor 3.386) DOI: doi.org/10.1016/j.ijforecast.2020.02.005
Paper Accepted for IEEE ITS
The paper “Improving Smart Charging Prioritization By Predicting Electric Vehicle Departure Time” by Oliver Frendo, Nadine Gaertner and Heiner Stuckenschmidt has been accepted for IEEE Transactions on Intelligent Transportation Systems (Impact Factor 5.744)
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.
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