Bernhard Pfahringer

According to our database1, Bernhard Pfahringer authored at least 165 papers between 1985 and 2021.

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

Timeline

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Bibliography

2021
Regularisation of neural networks by enforcing Lipschitz continuity.
Mach. Learn., 2021

Classifier Chains: A Review and Perspectives.
J. Artif. Intell. Res., 2021

PolyLM: Learning about Polysemy through Language Modeling.
CoRR, 2021

2020
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning.
Mach. Learn., 2020

Machine Learning (In) Security: A Stream of Problems.
CoRR, 2020

Seeing The Whole Patient: Using Multi-Label Medical Text Classification Techniques to Enhance Predictions of Medical Codes.
CoRR, 2020

A review of Automatic end-to-end De-Identification: Is High Accuracy the Only Metric?
Appl. Artif. Intell., 2020

confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms.
Proceedings of the Learning and Intelligent Optimization - 14th International Conference, 2020

Adaptive XGBoost for Evolving Data Streams.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

On Ensemble Techniques for Data Stream Regression.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams.
Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning.
Proceedings of the AI 2020: Advances in Artificial Intelligence, 2020

Transfer of Pretrained Model Weights Substantially Improves Semi-supervised Image Classification.
Proceedings of the AI 2020: Advances in Artificial Intelligence, 2020

Comparing High Dimensional Word Embeddings Trained on Medical Text to Bag-of-Words for Predicting Medical Codes.
Proceedings of the Intelligent Information and Database Systems - 12th Asian Conference, 2020

2019
Correction to: Adaptive random forests for evolving data stream classification.
Mach. Learn., 2019

AffectiveTweets: a Weka Package for Analyzing Affect in Tweets.
J. Mach. Learn. Res., 2019

Boosting decision stumps for dynamic feature selection on data streams.
Inf. Syst., 2019

Merit-guided dynamic feature selection filter for data streams.
Expert Syst. Appl., 2019

Automatic end-to-end De-identification: Is high accuracy the only metric?
CoRR, 2019

An ELMo-inspired approach to SemDeep-5's Word-in-Context task.
Proceedings of the 5th Workshop on Semantic Deep Learning, 2019

Towards Automated Configuration of Stream Clustering Algorithms.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Ensembles of Nested Dichotomies with Multiple Subset Evaluation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

On Calibration of Nested Dichotomies.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

XOR-Based Boolean Matrix Decomposition.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Feature Scoring using Tree-Based Ensembles for Evolving Data Streams.
Proceedings of the 2019 IEEE International Conference on Big Data (Big Data), 2019

Semi-supervised Learning Using Siamese Networks.
Proceedings of the AI 2019: Advances in Artificial Intelligence, 2019

Investigating the effect of novel classes in semi-supervised learning.
Proceedings of The 11th Asian Conference on Machine Learning, 2019

Stochastic Gradient Trees.
Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018
Transferring sentiment knowledge between words and tweets.
Web Intell., 2018

The online performance estimation framework: heterogeneous ensemble learning for data streams.
Mach. Learn., 2018

A survey of automatic de-identification of longitudinal clinical narratives.
CoRR, 2018

On the Calibration of Nested Dichotomies for Large Multiclass Tasks.
CoRR, 2018

Iterative subset selection for feature drifting data streams.
Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Deep Holistic Representation Learning from EHR.
Proceedings of the 12th International Symposium on Medical Information and Communication Technology, 2018

Combining active learning with concept drift detection for data stream mining.
Proceedings of the IEEE International Conference on Big Data, 2018

2017
Disjunctive Normal Form.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Conjunctive Normal Form.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Adaptive random forests for evolving data stream classification.
Mach. Learn., 2017

A survey on feature drift adaptation: Definition, benchmark, challenges and future directions.
J. Syst. Softw., 2017

Extremely Fast Decision Tree Mining for Evolving Data Streams.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Dynamic and Heterogeneous Ensembles for Time Series Forecasting.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Learning Through Utility Optimization in Regression Tasks.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Static techniques for reducing memory usage in the C implementation of whiley programs.
Proceedings of the Australasian Computer Science Week Multiconference, 2017

Probability Calibration Trees.
Proceedings of The 9th Asian Conference on Machine Learning, 2017

2016
Building a Twitter opinion lexicon from automatically-annotated tweets.
Knowl. Based Syst., 2016

MEKA: A Multi-label/Multi-target Extension to WEKA.
J. Mach. Learn. Res., 2016

Bound Analysis for Whiley Programs.
Electron. Notes Theor. Comput. Sci., 2016

From Opinion Lexicons to Sentiment Classification of Tweets and Vice Versa: A Transfer Learning Approach.
Proceedings of the 2016 IEEE/WIC/ACM International Conference on Web Intelligence, 2016

Determining Word-Emotion Associations from Tweets by Multi-label Classification.
Proceedings of the 2016 IEEE/WIC/ACM International Conference on Web Intelligence, 2016

Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

On Dynamic Feature Weighting for Feature Drifting Data Streams.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Annotate-Sample-Average (ASA): A New Distant Supervision Approach for Twitter Sentiment Analysis.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Learning Distance Metrics for Multi-Label Classification.
Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015
Evaluation methods and decision theory for classification of streaming data with temporal dependence.
Mach. Learn., 2015

Resampling strategies for regression.
Expert Syst. J. Knowl. Eng., 2015

Learning Similarity Metrics by Factorising Adjacency Matrices.
CoRR, 2015

From Unlabelled Tweets to Twitter-specific Opinion Words.
Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015

On a Few Recent Developments in Meta-Learning for Algorithm Ranking and Selection.
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015

Efficient Online Evaluation of Big Data Stream Classifiers.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Use of ensembles of Fourier spectra in capturing recurrent concepts in data streams.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Positive, Negative, or Neutral: Learning an Expanded Opinion Lexicon from Emoticon-Annotated Tweets.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Having a Blast: Meta-Learning and Heterogeneous Ensembles for Data Streams.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

2014
Active Learning With Drifting Streaming Data.
IEEE Trans. Neural Networks Learn. Syst., 2014

Pruning Incremental Linear Model Trees with Approximate Lookahead.
IEEE Trans. Knowl. Data Eng., 2014

Change detection in categorical evolving data streams.
Proceedings of the Symposium on Applied Computing, 2014

Hierarchical Meta-Rules for Scalable Meta-Learning.
Proceedings of the PRICAI 2014: Trends in Artificial Intelligence, 2014

High density-focused uncertainty sampling for active learning over evolving stream data.
Proceedings of the 3rd International Workshop on Big Data, 2014

Détection de changements dans des flots de données qualitatives.
Proceedings of the 14èmes Journées Francophones Extraction et Gestion des Connaissances, 2014

Towards Meta-learning over Data Streams.
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014

Algorithm Selection on Data Streams.
Proceedings of the Discovery Science - 17th International Conference, 2014

2013
Pairwise meta-rules for better meta-learning-based algorithm ranking.
Mach. Learn., 2013

Model selection based product kernel learning for regression on graphs.
Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013

Efficient data stream classification via probabilistic adaptive windows.
Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013

Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Towards a Framework for Designing Full Model Selection and Optimization Systems.
Proceedings of the Multiple Classifier Systems, 11th International Workshop, 2013

A Direct Policy-Search Algorithm for Relational Reinforcement Learning.
Proceedings of the Inductive Logic Programming - 23rd International Conference, 2013

CD-MOA: Change Detection Framework for Massive Online Analysis.
Proceedings of the Advances in Intelligent Data Analysis XII, 2013

SMOTE for Regression.
Proceedings of the Progress in Artificial Intelligence, 2013

Clustering Based Active Learning for Evolving Data Streams.
Proceedings of the Discovery Science - 16th International Conference, 2013

The MOA Data Stream Mining Tool: A Mid-Term Report.
Proceedings of the Workshop on Machine Learning for Sensory Data Analysis, 2013

Propositionalisation of Multi-instance Data Using Random Forests.
Proceedings of the AI 2013: Advances in Artificial Intelligence, 2013

2012
Ensembles of Restricted Hoeffding Trees.
ACM Trans. Intell. Syst. Technol., 2012

Experiment databases - A new way to share, organize and learn from experiments.
Mach. Learn., 2012

Scalable and efficient multi-label classification for evolving data streams.
Mach. Learn., 2012

Multi-label classification using boolean matrix decomposition.
Proceedings of the ACM Symposium on Applied Computing, 2012

Maximum Common Subgraph based locally weighted regression.
Proceedings of the ACM Symposium on Applied Computing, 2012

Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data.
Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

Full model selection in the space of data mining operators.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Stream Data Mining Using the MOA Framework.
Proceedings of the Database Systems for Advanced Applications, 2012

Bagging Ensemble Selection for Regression.
Proceedings of the AI 2012: Advances in Artificial Intelligence, 2012

2011
Classifier chains for multi-label classification.
Mach. Learn., 2011

MOA Concept Drift Active Learning Strategies for Streaming Data.
Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

Streaming Multi-label Classification.
Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

Detecting Sentiment Change in Twitter Streaming Data.
Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

Active Learning with Evolving Streaming Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

MOA: A Real-Time Analytics Open Source Framework.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

An effective evaluation measure for clustering on evolving data streams.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Mining frequent closed graphs on evolving data streams.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data.
Proceedings of the Discovery Science - 14th International Conference, 2011

Using the online cross-entropy method to learn relational policies for playing different games.
Proceedings of the 2011 IEEE Conference on Computational Intelligence and Games, 2011

Bagging Ensemble Selection.
Proceedings of the AI 2011: Advances in Artificial Intelligence, 2011

Semi-random Model Tree Ensembles: An Effective and Scalable Regression Method.
Proceedings of the AI 2011: Advances in Artificial Intelligence, 2011

2010
Conjunctive Normal Form.
Proceedings of the Encyclopedia of Machine Learning, 2010

Weka-A Machine Learning Workbench for Data Mining.
Proceedings of the Data Mining and Knowledge Discovery Handbook, 2nd ed., 2010

WEKA - Experiences with a Java Open-Source Project.
J. Mach. Learn. Res., 2010

MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

MOA: Massive Online Analysis.
J. Mach. Learn. Res., 2010

Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking.
Proceedings of the 2nd Asian Conference on Machine Learning, 2010

Leveraging Bagging for Evolving Data Streams.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Fast Perceptron Decision Tree Learning from Evolving Data Streams.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2010

Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA.
Proceedings of the ICDMW 2010, 2010

2009
The WEKA data mining software: an update.
SIGKDD Explor., 2009

New ensemble methods for evolving data streams.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Relational Random Forests Based on Random Relational Rules.
Proceedings of the IJCAI 2009, 2009

The Positive Effects of Negative Information: Extending One-Class Classification Models in Binary Proteomic Sequence Classification.
Proceedings of the AI 2009: Advances in Artificial Intelligence, 2009

Improving Adaptive Bagging Methods for Evolving Data Streams.
Proceedings of the Advances in Machine Learning, 2009

2008
Learning from the Past with Experiment Databases.
Proceedings of the PRICAI 2008: Trends in Artificial Intelligence, 2008

Handling Numeric Attributes in Hoeffding Trees.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

Exploiting Propositionalization Based on Random Relational Rules for Semi-supervised Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

Organizing the World's Machine Learning Information.
Proceedings of the Leveraging Applications of Formal Methods, 2008

Multi-label Classification Using Ensembles of Pruned Sets.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Mining Arbitrarily Large Datasets Using Heuristic k-Nearest Neighbour Search.
Proceedings of the AI 2008: Advances in Artificial Intelligence, 2008

Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis.
Proceedings of the AI 2008: Advances in Artificial Intelligence, 2008

2007
Scaling Up Semi-supervised Learning: An Efficient and Effective LLGC Variant.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2007

Clustering Relational Data Based on Randomized Propositionalization.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

New Options for Hoeffding Trees.
Proceedings of the AI 2007: Advances in Artificial Intelligence, 2007

2006
Improving on Bagging with Input Smearing.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2006

Using Weighted Nearest Neighbor to Benefit from Unlabeled Data.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2006

2005
Stress-Testing Hoeffding Trees.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Cache Hierarchy Inspired Compression: a Novel Architecture for Data Streams.
Proceedings of the 4th International Conference on IT in Asia, 2005

WEKA - A Machine Learning Workbench for Data Mining.
Proceedings of the Data Mining and Knowledge Discovery Handbook., 2005

2004
The Weka solution to the 2004 KDD Cup.
SIGKDD Explor., 2004

Experiments In Predicting Biodegradability.
Appl. Artif. Intell., 2004

A Toolbox for Learning from Relational Data with Propositional and Multi-instance Learners.
Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004

Clustering Large Datasets Using Cobweb and K-Means in Tandem.
Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004

Multinomial Naive Bayes for Text Categorization Revisited.
Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004

2003
Locally Weighted Naive Bayes.
Proceedings of the UAI '03, 2003

Text Categorisation Using Document Profiling.
Proceedings of the Knowledge Discovery in Databases: PKDD 2003, 2003

A Two-Level Learning Method for Generalized Multi-instance Problems.
Proceedings of the Machine Learning: ECML 2003, 2003

2002
Tabling Structures for Bottom-Up Logic Programming.
Proceedings of the Logic Based Program Synthesis and Tranformation, 2002

Multiclass Alternating Decision Trees.
Proceedings of the Machine Learning: ECML 2002, 2002

2001
Prediction of Ordinal Classes Using Regression Trees.
Fundam. Informaticae, 2001

Optimizing the Induction of Alternating Decision Trees.
Proceedings of the Knowledge Discovery and Data Mining, 2001

Wrapping Boosters against Noise.
Proceedings of the AI 2001: Advances in Artificial Intelligence, 2001

2000
Winning the KDD99 Classification Cup: Bagged Boosting.
SIGKDD Explor., 2000

Searching for Patterns in Political Event Sequences: Experiments with the Keds Database.
Cybern. Syst., 2000

Meta-Learning by Landmarking Various Learning Algorithms.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Learning to Use Operational Advice.
Proceedings of the ECAI 2000, 2000

1998
Guest Editorial: First-Order Knowledge Discovery in Databases.
Appl. Artif. Intell., 1998

Stochastic Propositionalization of Non-determinate Background Knowledge.
Proceedings of the Inductive Logic Programming, 8th International Workshop, 1998

1997
Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail.
Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

Compression-Based Pruning of Decision Lists.
Proceedings of the Machine Learning: ECML-97, 1997

1996
Efficient Search for Strong Partial Determinations.
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

1995
Compression-Based Evaluation of Partial Determinations.
Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995

Compression-Based Discretization of Continuous Attributes.
Proceedings of the Machine Learning, 1995

A New MDL Measure for Robust Rule Induction (Extended Abstract).
Proceedings of the Machine Learning: ECML-95, 1995

1994
Robust Constructive Induction.
Proceedings of the KI-94: Advances in Artificial Intelligence, 1994

Controlling Constructive Induction in CIPF: An MDL Approach.
Proceedings of the Machine Learning: ECML-94, 1994

1992
The Logical Way to Build a DL-based KR System.
Proceedings of the Issues in Description Logics: Users Meet Developers, 1992

1991
VIE-DU: Dialogue by Unification.
Proceedings of the Proc. 7th Austrian Conference on Artificial Intelligence, 1991

1989
Extending Explanation-Based Generalization.
Proceedings of the 5. Österreichische Artificial Intelligence-Tagung, 1989

1988
A decision support system for village health workers in developing countries.
Appl. Artif. Intell., 1988

1985
VIE-KET: Frames + Prolog.
Proceedings of the Österreichische Artificial Intelligence-Tagung, 1985


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