Georg Krempl

Joop Snijder

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023

Tutorial: Interactive Adaptive Learning.

[BibT_eX]

[DOI]

Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023), 2023

2022

Stream-based active learning for sliding windows under the influence of verification latency.

[BibT_eX]

[DOI]

Mach. Learn., 2022

A Stopping Criterion for Transductive Active Learning.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021

Implementation of and experimental software for active selection of classification features.

[BibT_eX]

[DOI]

Thomas T. Kok

Hugo G. Schnack

Softw. Impacts, 2021

Toward optimal probabilistic active learning using a Bayesian approach.

[BibT_eX]

[DOI]

Mach. Learn., 2021

ACE: A Novel Approach for the Statistical Analysis of Pairwise Connectivity.

[BibT_eX]

[DOI]

Tuan Pham Minh

CoRR, 2021

Probabilistic Active Learning for Active Class Selection.

[BibT_eX]

[DOI]

Cornelius Styp von Rekowski

Marianne Stecklina

CoRR, 2021

Active Selection of Classification Features.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XIX, 2021

Statistical Analysis of Pairwise Connectivity.

[BibT_eX]

[DOI]

Tuan Pham

Proceedings of the Discovery Science - 24th International Conference, 2021

2020

Beyond Adaptation: Understanding Distributional Changes (Dagstuhl Seminar 20372).

[BibT_eX]

[DOI]

Dagstuhl Reports, 2020

Constructing and predicting school advice for academic achievement: a comparison of item response theory and machine learning techniques.

[BibT_eX]

[DOI]

Matthieu J. S. Brinkhuis

Proceedings of the LAK '20: 10th International Conference on Learning Analytics and Knowledge, 2020

2019

Temporal density extrapolation using a dynamic basis approach.

[BibT_eX]

[DOI]

Dominik Lang

Data Min. Knowl. Discov., 2019

2017

Probabilistic Active Learning with Structure-Sensitive Kernels.

[BibT_eX]

[DOI]

Dominik Lang

Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), 2017

Challenges of Reliable, Realistic and Comparable Active Learning Evaluation.

[BibT_eX]

[DOI]

2016

Aktives maschinelles Lernen bei unvollständiger Information

[BibT_eX]

[DOI]

PhD thesis, 2016

Investigating Exploratory Capabilities of Uncertainty Sampling using SVMs in Active Learning.

[BibT_eX]

[DOI]

Proceedings of the Workshop on Active Learning: Applications, 2016

Active Subtopic Detection in Multitopic Data.

[BibT_eX]

[DOI]

Benjamin Bergner

Proceedings of the Workshop on Active Learning: Applications, 2016

Multi-Class Probabilistic Active Learning.

[BibT_eX]

[DOI]

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015

Optimised probabilistic active learning (OPAL) - For fast, non-myopic, cost-sensitive active classification.

[BibT_eX]

[DOI]

Vincent Lemaire

Mach. Learn., 2015

Predicting the post-treatment recovery of patients suffering from traumatic brain injury (TBI).

[BibT_eX]

[DOI]

Zaigham Faraz Siddiqui

Brain Informatics, 2015

Temporal Density Extrapolation.

[BibT_eX]

[DOI]

Proceedings of the 1st International Workshop on Advanced Analytics and Learning on Temporal Data, 2015

How to select information that matters: a comparative study on active learning strategies for classification.

[BibT_eX]

[DOI]

Christian Beyer

Vincent Lemaire

Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business, 2015

Probabilistic Active Learning in Datastreams.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

Clustering-Based Optimised Probabilistic Active Learning (COPAL).

[BibT_eX]

[DOI]

Tuan Cuong Ha

Proceedings of the Discovery Science - 18th International Conference, 2015

2014

Open challenges for data stream mining research.

[BibT_eX]

[DOI]

SIGKDD Explor., 2014

Probabilistic Active Learning: A Short Proposition.

[BibT_eX]

[DOI]

Proceedings of the ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, 2014

Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science - 17th International Conference, 2014

Are Some Brain Injury Patients Improving More Than Others?

[BibT_eX]

[DOI]

Zaigham Faraz Siddiqui

Proceedings of the Brain Informatics and Health - International Conference, 2014

2013

Drift mining in data: A framework for addressing drift in classification.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2013

Correcting the Usage of the Hoeffding Inequality in Stream Mining.

[BibT_eX]

[DOI]

Pawel Matuszyk

Proceedings of the Advances in Intelligent Data Analysis XII, 2013

2012

A hierarchical tree layout algorithm with an application to corporate management in a change process.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2012

2011

Online Clustering of High-Dimensional Trajectories under Concept Drift.

[BibT_eX]

[DOI]

Zaigham Faraz Siddiqui

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Drift Models and Classification in Presence of Latency and Drift.

[BibT_eX]

Proceedings of the Report of the symposium "Lernen, 2011

The Algorithm APT to Classify in Concurrence of Latency and Drift.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis X - 10th International Symposium, 2011

Classification in Presence of Drift and Latency.

[BibT_eX]

[DOI]

Proceedings of the Data Mining Workshops (ICDMW), 2011

2009

Partitioner Trees for Classification: A New Ensemble Method.

[BibT_eX]

[DOI]