5 citations · 15 across the 12 of their papers we have counts for
12 papers
OPTWIN: Drift identification with optimal sub-windows
Mauro Dalle Lucca Tosi, Martin Theobald
Online Learning (OL) is a field of research that is increasingly gaining attention both in academia and industry. One of the main challenges of OL is the inherent presence of conce…
Enriching Relation Extraction with OpenIE
Alessandro Temperoni, Maria Biryukov, Martin Theobald
Relation extraction (RE) is a sub-discipline of information extraction (IE) which focuses on the prediction of a relational predicate from a natural-language input unit (such as a…
BigText-QA: Question Answering over a Large-Scale Hybrid Knowledge Graph
Jingjing Xu, Maria Biryukov, Martin Theobald +1
Answering complex questions over textual resources remains a challenge, particularly when dealing with nuanced relationships between multiple entities expressed within natural-lang…
TensAIR: Real-Time Training of Neural Networks from Data-streams
Mauro D. L. Tosi, Vinu E. Venugopal, Martin Theobald
Online learning (OL) from data streams is an emerging area of research that encompasses numerous challenges from stream processing, machine learning, and networking. Stream-process…
Robust and Provable Guarantees for Sparse Random Embeddings
Maciej Skorski, Alessandro Temperoni, Martin Theobald
In this work, we improve upon the guarantees for sparse random embeddings, as they were recently provided and analyzed by Freksen at al. (NIPS'18) and Jagadeesan (NIPS'19). Specifi…
AIR: A Light-Weight Yet High-Performance Dataflow Engine based on Asynchronous Iterative Routing
Vinu E. Venugopal, Martin Theobald, Samira Chaychi +1
Distributed Stream Processing Systems (DSPSs) are among the currently most emerging topics in data management, with applications ranging from real-time event monitoring to processi…
Lineage-Aware Temporal Windows: Supporting Set Operations in Temporal-Probabilistic Databases
Katerina Papaioannou, Martin Theobald, Michael H. Böhlen
In temporal-probabilistic (TP) databases, the combination of the temporal and the probabilistic dimension adds significant overhead to the computation of set operations. Although s…
Generalized Lineage-Aware Temporal Windows: Supporting Outer and Anti Joins in Temporal-Probabilistic Databases
Katerina Papaioannou, Martin Theobald, Michael Böhlen
The result of a temporal-probabilistic (TP) join with negation includes, at each time point, the probability with which a tuple of a positive relation matches none of the…
A General Framework for Anytime Approximation in Probabilistic Databases
Maarten Van den Heuvel, Floris Geerts, Wolfgang Gatterbauer +1
Anytime approximation algorithms that compute the probabilities of queries over probabilistic databases can be of great use to statistical learning tasks. Those approaches have bee…
Learning Tuple Probabilities
Maximilian Dylla, Martin Theobald
Learning the parameters of complex probabilistic-relational models from labeled training data is a standard technique in machine learning, which has been intensively studied in the…
Distributed Processing of Generalized Graph-Pattern Queries in SPARQL 1.1
Sairam Gurajada, Martin Theobald
We propose an efficient and scalable architecture for processing generalized graph-pattern queries as they are specified by the current W3C recommendation of the SPARQL 1.1 "Query…
Proceedings of the first International Workshop On Open Data, WOD-2012
Guillaume Raschia, Martin Theobald, Ioana Manolescu
WOD-2012 aims at facilitating new trends and ideas from a broad range of topics concerned within the widely-spread Open Data movement, from the viewpoint of computer science resear…