Ammar Shaker

Affiliations:
  • University of Paderborn, Department of Computer Science, Germany


According to our database1, Ammar Shaker authored at least 30 papers between 2010 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Multi-Source Survival Domain Adaptation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Human-Centric Research for NLP: Towards a Definition and Guiding Questions.
CoRR, 2022

A Human-Centric Assessment Framework for AI.
CoRR, 2022

Modular-Relatedness for Continual Learning.
Proceedings of the Advances in Intelligent Data Analysis XX, 2022

Uncertainty Propagation in Node Classification.
Proceedings of the IEEE International Conference on Data Mining, 2022

MILIE: Modular & Iterative Multilingual Open Information Extraction.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Learning to Transfer with von Neumann Conditional Divergence.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
TSK-Streams: learning TSK fuzzy systems for regression on data streams.
Data Min. Knowl. Discov., 2021

Learning to Transfer with von Neumann Conditional Divergence.
CoRR, 2021

Bilevel Continual Learning.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
Learning an Interpretable Graph Structure in Multi-Task Learning.
CoRR, 2020

Towards Interpretable Multi-task Learning Using Bilevel Programming.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Online Meta-Forest for Regression Data Streams.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
TSK-Streams: Learning TSK Fuzzy Systems on Data Streams.
CoRR, 2019

Efficient and Scalable Multi-Task Regression on Massive Number of Tasks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
MetaBags: Bagged Meta-Decision Trees for Regression.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

2017
Novel methods for mining and learning from data streams
PhD thesis, 2017

Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.
IEEE Trans. Software Eng., 2017

Learning TSK Fuzzy Rules from Data Streams.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2015
Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study.
Neurocomputing, 2015

2014
Open challenges for data stream mining research.
SIGKDD Explor., 2014

Self-adaptive and local strategies for a smooth treatment of drifts in data streams.
Evol. Syst., 2014

Survival analysis on data streams: Analyzing temporal events in dynamically changing environments.
Int. J. Appl. Math. Comput. Sci., 2014

2013
Evolving fuzzy pattern trees for binary classification on data streams.
Inf. Sci., 2013

Resolving global and local drifts in data stream regression using evolving rule-based models.
Proceedings of the 2013 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2013

Recovery Analysis for Adaptive Learning from Non-stationary Data Streams.
Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013, 2013

2012
IBLStreams: a system for instance-based classification and regression on data streams.
Evol. Syst., 2012

2011
On-line elimination of local redundancies in evolving fuzzy systems.
Evol. Syst., 2011

2010
SciPlore Xtract: Extracting Titles from Scientific PDF Documents by Analyzing Style Information (Font Size).
Proceedings of the Research and Advanced Technology for Digital Libraries, 2010


  Loading...