Peter A. Flach

Orcid: 0000-0001-6857-5810

Affiliations:
  • University of Bristol, Department of Computer Science, UK
  • Tilburg University, The Netherlands


According to our database1, Peter A. Flach authored at least 213 papers between 1989 and 2024.

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

Timeline

Legend:

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Bibliography

2024
Interpretable representations in explainable AI: from theory to practice.
Data Min. Knowl. Discov., September, 2024

Explaining a Probabilistic Prediction on the Simplex with Shapley Compositions.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023
An active semi-supervised deep learning model for human activity recognition.
J. Ambient Intell. Humaniz. Comput., October, 2023

Classifier calibration: a survey on how to assess and improve predicted class probabilities.
Mach. Learn., September, 2023

Co-designing opportunities for Human-Centred Machine Learning in supporting Type 1 diabetes decision-making.
Int. J. Hum. Comput. Stud., May, 2023

Simply Logical - The First Three Decades.
Proceedings of the Prolog: The Next 50 Years, 2023

Shapley Sets: Feature Attribution via Recursive Function Decomposition.
CoRR, 2023

MIDI-Draw: Sketching to Control Melody Generation.
CoRR, 2023

When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations.
Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2023

Reconciling Training and Evaluation Objectives in Location Agnostic Surrogate Explainers.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
FAT Forensics: A Python toolbox for algorithmic fairness, accountability and transparency.
Softw. Impacts, December, 2022

What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components.
Dataset, October, 2022

Simply Logical - Intelligent Reasoning by Example (Fully Interactive Online Edition).
Dataset, August, 2022

Empirical Evaluation of Predictive Models: A keynote at ECIR 2022.
SIGIR Forum, June, 2022

What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components.
CoRR, 2022

Simply Logical - Intelligent Reasoning by Example (Fully Interactive Online Edition).
CoRR, 2022

The Weak Supervision Landscape.
Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2022

Understanding Reinforcement Learning Based Localisation as a Probabilistic Inference Algorithm.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Self-Enhancer: A Self-supervised Framework for Low-Supervision, Drifted Data with Significant Missing Values.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

LIMESegment: Meaningful, Realistic Time Series Explanations.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories.
IEEE Trans. Knowl. Data Eng., 2021

Human Activity Recognition Based on Dynamic Active Learning.
IEEE J. Biomed. Health Informatics, 2021

Co-Designing Personal Health? Multidisciplinary Benefits and Challenges in Informing Diabetes Self-Care Technologies.
Proc. ACM Hum. Comput. Interact., 2021

Multi-label thresholding for cost-sensitive classification.
Neurocomputing, 2021

Efficient and Robust Model Benchmarks with Item Response Theory and Adaptive Testing.
Int. J. Interact. Multim. Artif. Intell., 2021

Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence.
CoRR, 2021

Classifier Calibration: How to assess and improve predicted class probabilities: a survey.
CoRR, 2021

Risk Sensitive Model-Based Reinforcement Learning using Uncertainty Guided Planning.
CoRR, 2021

You Only Write Thrice: Creating Documents, Computational Notebooks and Presentations From a Single Source.
CoRR, 2021

Continual Density Ratio Estimation in an Online Setting.
CoRR, 2021

Machine Learning Explanations as Boundary Objects: How AI Researchers Explain and Non-Experts Perceive Machine Learning.
Proceedings of the Joint Proceedings of the ACM IUI 2021 Workshops co-located with 26th ACM Conference on Intelligent User Interfaces (ACM IUI 2021), 2021

2020
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems.
Dataset, May, 2020

Reflections on reciprocity in research.
Mach. Learn., 2020

One Explanation Does Not Fit All.
Künstliche Intell., 2020

FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems.
J. Open Source Softw., 2020

Modelling Patient Behaviour Using IoT Sensor Data: a Case Study to Evaluate Techniques for Modelling Domestic Behaviour in Recovery from Total Hip Replacement Surgery.
J. Heal. Informatics Res., 2020

Uni- and multivariate probability density models for numeric subgroup discovery.
Intell. Data Anal., 2020

Model-Based Reinforcement Learning for Type 1Diabetes Blood Glucose Control.
CoRR, 2020

Towards Faithful and Meaningful Interpretable Representations.
CoRR, 2020

Bypassing Gradients Re-Projection with Episodic Memories in Online Continual Learning.
CoRR, 2020

LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees.
CoRR, 2020

One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency.
CoRR, 2020

Polsar Image Classification via Robust Low-Rank Feature Extraction and Markov Random Field.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Explainability fact sheets: a framework for systematic assessment of explainable approaches.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Model-Based Reinforcement Learning for Type 1 Diabetes Blood Glucose Control.
Proceedings of the First International AAI4H, 2020

FACE: Feasible and Actionable Counterfactual Explanations.
Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2019
An application of hierarchical Gaussian processes to the detection of anomalies in star light curves.
Neurocomputing, 2019

Setting decision thresholds when operating conditions are uncertain.
Data Min. Knowl. Discov., 2019

bLIMEy: Surrogate Prediction Explanations Beyond LIME.
CoRR, 2019

Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration.
CoRR, 2019

HyperStream: a Workflow Engine for Streaming Data.
CoRR, 2019

β<sup>3</sup>-IRT: A New Item Response Model and its Applications.
CoRR, 2019

A Big Data platform for smart meter data analytics.
Comput. Ind., 2019

Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Distribution calibration for regression.
Proceedings of the 36th International Conference on Machine Learning, 2019

$β^3$-IRT: A New Item Response Model and its Applications.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Desiderata for Interpretability: Explaining Decision Tree Predictions with Counterfactuals.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Counterfactual Explanations of Machine Learning Predictions: Opportunities and Challenges for AI Safety.
Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the Thirty-Third AAAI Conference on Artificial Intelligence 2019 (AAAI-19), 2019

Performance Evaluation in Machine Learning: The Good, the Bad, the Ugly, and the Way Forward.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Activities of Daily Living Ontology for Ubiquitous Systems: Development and Evaluation.
Sensors, 2018

A Comprehensive Study of Activity Recognition Using Accelerometers.
Informatics, 2018

Introduction to the special issue on Data Science in Europe.
Int. J. Data Sci. Anal., 2018

Non-Parametric Calibration of Probabilistic Regression.
CoRR, 2018

Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Glass-Box: Explaining AI Decisions With Counterfactual Statements Through Conversation With a Voice-enabled Virtual Assistant.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Conversational Explanations of Machine Learning Predictions Through Class-contrastive Counterfactual Statements.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

The Facets of Artificial Intelligence: A Framework to Track the Evolution of AI.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Analysis of Patient Domestic Activity in Recovery From Hip or Knee RePlacement Surgery: Modelling Wrist-worn Wearable RSSI and Accelerometer Data in The Wild.
Proceedings of the 3rd International Workshop on Knowledge Discovery in Healthcare Data co-located with the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018), 2018

Anomaly detection in star light curves using hierarchical Gaussian processes.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017
ROC Analysis.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

First-Order Logic.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Classifier Calibration.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Unsupervised learning of sensor topologies for improving activity recognition in smart environments.
Neurocomputing, 2017

CASP-DM: Context Aware Standard Process for Data Mining.
CoRR, 2017

Probabilistic Sensor Fusion for Ambient Assisted Living.
CoRR, 2017

Computational support for academic peer review: a perspective from artificial intelligence.
Commun. ACM, 2017

The Role of Textualisation and Argumentation in Understanding the Machine Learning Process.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Feature Construction and Calibration for Clustering Daily Load Curves from Smart-Meter Data.
IEEE Trans. Ind. Informatics, 2016

On the need for structure modelling in sequence prediction.
Mach. Learn., 2016

Cost-sensitive boosting algorithms: Do we really need them?
Mach. Learn., 2016

The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data.
CoRR, 2016

Reframing in context: A systematic approach for model reuse in machine learning.
AI Commun., 2016

Subgroup Discovery with Proper Scoring Rules.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

BDL.NET: Bayesian dictionary learning in Infer.NET.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Activity Recognition in Multiple Contexts for Smart-House Data.
Proceedings of the 26th International Conference on Inductive Logic Programming (Short papers), 2016

ADL™: A Topic Model for Discovery of Activities of Daily Living in a Smart Home.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Background Check: A General Technique to Build More Reliable and Versatile Classifiers.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Active transfer learning for activity recognition.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Declaratively Capturing Local Label Correlations with Multi-Label Trees.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015
Report of the First International Workshop on Learning over Multiple Contexts (LMCE 2014).
SIGKDD Explor., 2015

Bridging e-Health and the Internet of Things: The SPHERE Project.
IEEE Intell. Syst., 2015

Model Reuse with Subgroup Discovery.
Proceedings of the ECML/PKDD 2015 Discovery Challenges co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2015), 2015

Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Bayesian Modelling of the Temporal Aspects of Smart Home Activity with Circular Statistics.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

SVR-based Modelling for the MoReBikeS Challenge: Analysis, Visualisation and Prediction.
Proceedings of the ECML/PKDD 2015 Discovery Challenges co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2015), 2015

Versatile Decision Trees for Learning Over Multiple Contexts.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Precision-Recall-Gain Curves: PR Analysis Done Right.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Activity recognition using conditional random field.
Proceedings of the 2nd international Workshop on Sensor-based Activity Recognition and Interaction, 2015

Reframing in Frequent Pattern Mining.
Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015

2014
Subgroup Discovery in Smart Electricity Meter Data.
IEEE Trans. Ind. Informatics, 2014

Rate-Oriented Point-Wise Confidence Bounds for ROC Curves.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Rate-Constrained Ranking and the Rate-Weighted AUC.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Reliability Maps: A Tool to Enhance Probability Estimates and Improve Classification Accuracy.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

LaCova: A Tree-Based Multi-label Classifier Using Label Covariance as Splitting Criterion.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

A Machine Learning Approach to Objective Cardiac Event Detection.
Proceedings of the Eighth International Conference on Complex, 2014

2013
ROC curves in cost space.
Mach. Learn., 2013

Guest editors' introduction: special issue of selected papers from ECML-PKDD 2012.
Mach. Learn., 2013

SubSift web services and workflows for profiling and comparing scientists and their published works.
Future Gener. Comput. Syst., 2013

Guest editors' introduction: special section of selected papers from ECML-PKDD 2012.
Data Min. Knowl. Discov., 2013

A Higher-order data flow model for heterogeneous Big Data.
Proceedings of the 2013 IEEE International Conference on Big Data (IEEE BigData 2013), 2013

2012
ILP turns 20 - Biography and future challenges.
Mach. Learn., 2012

A unified view of performance metrics: translating threshold choice into expected classification loss.
J. Mach. Learn. Res., 2012

Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them).
Briefings Bioinform., 2012

Machine Learning - The Art and Science of Algorithms that Make Sense of Data.
Cambridge University Press, ISBN: 978-1-10-742222-3, 2012

2011
The Machine Learning journal: 25 years young.
Mach. Learn., 2011

Threshold Choice Methods: the Missing Link
CoRR, 2011

Generic Multiplicative Methods for Implementing Machine Learning Algorithms on MapReduce
CoRR, 2011

Technical Note: Towards ROC Curves in Cost Space
CoRR, 2011

Smooth Receiver Operating Characteristics (smROC) Curves.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Brier Curves: a New Cost-Based Visualisation of Classifier Performance.
Proceedings of the 28th International Conference on Machine Learning, 2011

A Coherent Interpretation of AUC as a Measure of Aggregated Classification Performance.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
ROC Analysis.
Proceedings of the Encyclopedia of Machine Learning, 2010

First-Order Logic.
Proceedings of the Encyclopedia of Machine Learning, 2010

The Machine Learning journal: 250 issues and counting.
Mach. Learn., 2010

SubSift: a novel application of the vector space model to support the academic research process.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

Exploiting the High Predictive Power of Multi-class Subgroups.
Proceedings of the 2nd Asian Conference on Machine Learning, 2010

First-Order Multi-class Subgroup Discovery.
Proceedings of the STAIRS 2010, 2010

Learning Multi-class Theories in ILP.
Proceedings of the Inductive Logic Programming - 20th International Conference, 2010

The Advantages of Seed Examples in First-Order Multi-class Subgroup Discovery.
Proceedings of the ECAI 2010, 2010

Ukwabelana - An open-source morphological Zulu corpus.
Proceedings of the COLING 2010, 2010

Enhanced Word Decomposition by Calibrating the Decision Threshold of Probabilistic Models and Using a Model Ensemble.
Proceedings of the ACL 2010, 2010

2009
Towards Learning Morphology for Under-Resourced Fusional and Agglutinating Languages.
IEEE Trans. Speech Audio Process., 2009

Novel tools to streamline the conference review process: experiences from SIGKDD'09.
SIGKDD Explor., 2009

Abduction and Induction in Artificial Intelligence.
J. Appl. Log., 2009

Evaluation Measures for Multi-class Subgroup Discovery.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Using Time Dependent Link Reduction to Improve the Efficiency of Topic Prediction in Co-Authorship Graphs.
Proceedings of the Complex Networks, 2009

PROMODES: A Probabilistic Generative Model for Word Decomposition.
Proceedings of the Working Notes for CLEF 2009 Workshop co-located with the 13th European Conference on Digital Libraries (ECDL 2009) , Corfù, Greece, September 30, 2009

Unsupervised Word Decomposition with the Promodes Algorithm.
Proceedings of the Multilingual Information Access Evaluation I. Text Retrieval Experiments, 2009

UNGRADE: UNsupervised GRAph DEcomposition.
Proceedings of the Working Notes for CLEF 2009 Workshop co-located with the 13th European Conference on Digital Libraries (ECDL 2009) , Corfù, Greece, September 30, 2009

Unsupervised Morpheme Discovery with Ungrade.
Proceedings of the Multilingual Information Access Evaluation I. Text Retrieval Experiments, 2009

Cost-Based Sampling of Individual Instances.
Proceedings of the Advances in Artificial Intelligence, 2009

2008
Learning the morphology of Zulu with different degrees of supervision.
Proceedings of the 2008 IEEE Spoken Language Technology Workshop, 2008

Querying and Merging Heterogeneous Data by Approximate Joins on Higher-Order Terms.
Proceedings of the Inductive Logic Programming, 18th International Conference, 2008

A Fast Method for Property Prediction in Graph-Structured Data from Positive and Unlabelled Examples.
Proceedings of the ECAI 2008, 2008

2007
Network analysis in natural sciences and engineering.
AI Commun., 2007

Putting Things in Order: On the Fundamental Role of Ranking in Classification and Probability Estimation.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

An Improved Model Selection Heuristic for AUC.
Proceedings of the Machine Learning: ECML 2007, 2007

A Simple Lexicographic Ranker and Probability Estimator.
Proceedings of the Machine Learning: ECML 2007, 2007

On classification, ranking, and probability estimation.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

2006
Towards Automating Simulation-Based Design Verification Using ILP.
Proceedings of the Inductive Logic Programming, 16th International Conference, 2006

Reinventing Machine Learning with ROC Analysis.
Proceedings of the Advances in Artificial Intelligence, 2006

2005
ROC 'n' Rule Learning - Towards a Better Understanding of Covering Algorithms.
Mach. Learn., 2005

A Response to Webb and Ting's <i>On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions</i>.
Mach. Learn., 2005

ROCCER: An Algorithm for Rule Learning Based on ROC Analysis.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Repairing Concavities in ROC Curves.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Combining Bayesian Networks with Higher-Order Data Representations.
Proceedings of the Advances in Intelligent Data Analysis VI, 2005

2004
Book review: Logic for Learning: Learning Comprehensible Theories from Structured Data by John W. Lloyd, Springer-Verlag, 2003, ISBN 3-540-42027-4.
Theory Pract. Log. Program., 2004

The 1st workshop on ROC analysis in artificial intelligence (ROCAI-2004).
SIGKDD Explor., 2004

Decision Support Through Subgroup Discovery: Three Case Studies and the Lessons Learned.
Mach. Learn., 2004

Kernels and Distances for Structured Data.
Mach. Learn., 2004

Naive Bayesian Classification of Structured Data.
Mach. Learn., 2004

Subgroup Discovery with CN2-SD.
J. Mach. Learn. Res., 2004

Hierarchical Bayesian Networks: An Approach to Classification and Learning for Structured Data.
Proceedings of the Methods and Applications of Artificial Intelligence, 2004

Delegating classifiers.
Proceedings of the Machine Learning, 2004

Redundant feature elimination for multi-class problems.
Proceedings of the Machine Learning, 2004

An Analysis of Stopping and Filtering Criteria for Rule Learning.
Proceedings of the Machine Learning: ECML 2004, 2004

2003
Improved Distances for Structured Data.
Proceedings of the Inductive Logic Programming: 13th International Conference, 2003

Comparative Evaluation of Approaches to Propositionalization.
Proceedings of the Inductive Logic Programming: 13th International Conference, 2003

Improving Accuracy and Cost of Two-class and Multi-class Probabilistic Classifiers Using ROC Curves.
Proceedings of the Machine Learning, 2003

An Analysis of Rule Evaluation Metrics.
Proceedings of the Machine Learning, 2003

The Geometry of ROC Space: Understanding Machine Learning Metrics through ROC Isometrics.
Proceedings of the Machine Learning, 2003

Improving the AUC of Probabilistic Estimation Trees.
Proceedings of the Machine Learning: ECML 2003, 2003

On Graph Kernels: Hardness Results and Efficient Alternatives.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
Web-based analysis of data mining and decision support education.
AI Commun., 2002

RSD: Relational Subgroup Discovery through First-Order Feature Construction.
Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

1BC2: A True First-Order Bayesian Classifier.
Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

Kernels for Structured Data.
Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

Multi-Instance Kernels.
Proceedings of the Machine Learning, 2002

Learning Decision Trees Using the Area Under the ROC Curve.
Proceedings of the Machine Learning, 2002

Adapting classification rule induction to subgroup discovery.
Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002), 2002

Improved Dataset Characterisation for Meta-learning.
Proceedings of the Discovery Science, 5th International Conference, 2002

Learning in Clausal Logic: A Perspective on Inductive Logic Programming.
Proceedings of the Computational Logic: Logic Programming and Beyond, 2002

2001
An extended transformation approach to inductive logic programming.
ACM Trans. Comput. Log., 2001

Confirmation-Guided Discovery of First-Order Rules with Tertius.
Mach. Learn., 2001

Editorial: Inductive Logic Programming is Coming of Age.
Mach. Learn., 2001

On the state of the art in machine learning: A personal review.
Artif. Intell., 2001

WBCsvm: Weighted Bayesian Classification based on Support Vector Machines.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Multi-relational Data Mining: a perspective.
Proceedings of the Progress in Artificial Intelligence, 2001

2000
Discovery of multivalued dependencies from relations.
Intell. Data Anal., 2000

The Use of Functional and Logic Languages in Machine Learning.
Proceedings of the 9th International Workshop on Functional and Logic Programming, 2000

Predictive Performance of Weghted Relative Accuracy.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2000

Decomposing Probability Distributions on Structured Individuals.
Proceedings of the Inductive Logic Programming, 10th International Conference, 2000

1999
Database Dependency Discovery: A Machine Learning Approach.
AI Commun., 1999

Rule Evaluation Measures: A Unifying View.
Proceedings of the Inductive Logic Programming, 9th International Workshop, 1999

IBC: A First-Order Bayesian Classifier.
Proceedings of the Inductive Logic Programming, 9th International Workshop, 1999

Knowledge Representation for Inductive Learning.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning and Uncertainty, 1999

1998
Conference Report: Abduction and Induction in AI; Logic, Proofs and Algorithms; Logic in Natural Language; Logic for Concurrency and Synchronisation (LOCUS).
Log. J. IGPL, 1998

Comparing Consequence Relations.
Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning (KR'98), 1998

Strongly Typed Inductive Concept Learning.
Proceedings of the Inductive Logic Programming, 8th International Workshop, 1998

From Extensional to Intensional Knowledge: Inductive Logic Programming Techniques and Their Application to Deductive Databases.
Proceedings of the Transactions and Change in Logic Databases, 1998

1997
Abductive and Inductive Reasoning: Report of the ECAI'96 Workshop.
Log. J. IGPL, 1997

Normal Forms for Inductive Logic Programming.
Proceedings of the Inductive Logic Programming, 7th International Workshop, 1997

Inductive Logic Databases: From Extensional to Intensional Knowledge.
Proceedings of the Deductive and Object-Oriented Databases, 5th International Conference, 1997

1996
Rationality Postulates for Induction.
Proceedings of the Sixth Conference on Theoretical Aspects of Rationality and Knowledge, 1996

1994
Simply logical - intelligent reasoning by example.
Wiley professional computing, Wiley, ISBN: 978-0-471-94152-1, 1994

1993
Predicate Invention in Inductive Data Engineering.
Proceedings of the Machine Learning: ECML-93, 1993

1992
A Model of Inductive Reasoning.
Proceedings of the Knowledge Representation and Reasoning Under Uncertainty, 1992

An Analysis of Various Forms of "Jumping to Conclusions".
Proceedings of the Analogical and Inductive Inference, 1992

1991
Towards a Theory of Inductive Logic Programming.
Proceedings of the Methodologies for Intelligent Systems, 6th International Symposium, 1991

Consistent Term Mappings, Term Partitions and Inverse Resolution.
Proceedings of the Machine Learning, 1991

1989
Second-order Inductive Learning.
Proceedings of the Analogical and Inductive Inference, 1989


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