Tijl De Bie

According to our database1, Tijl De Bie authored at least 128 papers between 2003 and 2022.

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Bibliography

2022
Graph-Survival: A Survival Analysis Framework for Machine Learning on Temporal Networks.
CoRR, 2022

Evaluating Feature Attribution Methods in the Image Domain.
CoRR, 2022

Optimal Transport of Binary Classifiers to Fairness.
CoRR, 2022

Automating data science.
Commun. ACM, 2022

2021
Stable topological signatures for metric trees through graph approximations.
Pattern Recognit. Lett., 2021

Conditional t-SNE: more informative t-SNE embeddings.
Mach. Learn., 2021

Mining explainable local and global subgraph patterns with surprising densities.
Data Min. Knowl. Discov., 2021

An Earth Mover's Distance Based Graph Distance Metric For Financial Statements.
CoRR, 2021

Topologically Regularized Data Embeddings.
CoRR, 2021

The Curse Revisited: a Newly Quantified Concept of Meaningful Distances for Learning from High-Dimensional Noisy Data.
CoRR, 2021

Automating Data Science: Prospects and Challenges.
CoRR, 2021

Explanations for Network Embedding-Based Link Predictions.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

Adversarial Robustness of Probabilistic Network Embedding for Link Prediction.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

The KL-Divergence Between a Graph Model and its Fair I-Projection as a Fairness Regularizer.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

2020
A Constrained Randomization Approach to Interactive Visual Data Exploration with Subjective Feedback.
IEEE Trans. Knowl. Data Eng., 2020

Mining Topological Structure in Graphs through Forest Representations.
J. Mach. Learn. Res., 2020

Interactive visual data exploration with subjective feedback: an information-theoretic approach.
Data Min. Knowl. Discov., 2020

SIAS-miner: mining subjectively interesting attributed subgraphs.
Data Min. Knowl. Discov., 2020

Relaxing the strong triadic closure problem for edge strength inference.
Data Min. Knowl. Discov., 2020

Network Representation Learning for Link Prediction: Are we improving upon simple heuristics?
CoRR, 2020

Scalable Dyadic Independence Models with Local and Global Constraints.
CoRR, 2020

ALPINE: Active Link Prediction using Network Embedding.
CoRR, 2020

Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Gibbs Sampling Subjectively Interesting Tiles.
Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

Graph Approximations to Geodesics on Metric Graphs.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

DeBayes: a Bayesian Method for Debiasing Network Embeddings.
Proceedings of the 37th International Conference on Machine Learning, 2020

FONDUE: Framework for Node Disambiguation Using Network Embeddings.
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress?
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

Block-Approximated Exponential Random Graphs.
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

CSNE: Conditional Signed Network Embedding.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

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

2019
Design and validation of an auditory biofeedback system for modification of running parameters.
J. Multimodal User Interfaces, 2019

SIMIT: Subjectively Interesting Motifs in Time Series.
Entropy, 2019

Subjectively interesting connecting trees and forests.
Data Min. Knowl. Discov., 2019

Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information.
CoRR, 2019

Mining Subjectively Interesting Attributed Subgraphs.
CoRR, 2019

ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions.
CoRR, 2019

Opinion Dynamics with Backfire Effect and Biased Assimilation.
CoRR, 2019

EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction.
Proceedings of the 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning co-located with SIAM International Conference on Data Mining (SDM 2019), 2019

Contrastive Antichains in Hierarchies.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Discovering Interesting Cycles in Directed Graphs.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Conditional Network Embeddings.
Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018
From raw audio to a seamless mix: creating an automated DJ system for Drum and Bass.
EURASIP J. Audio Speech Music. Process., 2018

SICA: subjectively interesting component analysis.
Data Min. Knowl. Discov., 2018

Automating Data Science (Dagstuhl Seminar 18401).
Dagstuhl Reports, 2018

From acquaintance to best friend forever: robust and fine-grained inference of social tie strengths.
CoRR, 2018

Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Ordinal Label Proportions.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

A biofeedback music-sonification system for gait retraining.
Proceedings of the 5th International Conference on Movement and Computing, 2018

Quantifying and Minimizing Risk of Conflict in Social Networks.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Subjectively Interesting Subgroup Discovery on Real-Valued Targets.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

2017
Subjectively Interesting Connecting Trees.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Hierarchical Novelty Detection.
Proceedings of the Advances in Intelligent Data Analysis XVI, 2017

2016
SuMoTED: An intuitive edit distance between rooted unordered uniquely-labelled trees.
Pattern Recognit. Lett., 2016

Subjective interestingness of subgraph patterns.
Mach. Learn., 2016

P-N-RMiner: a generic framework for mining interesting structured relational patterns.
Int. J. Data Sci. Anal., 2016

Interactive Visual Data Exploration with Subjective Feedback.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

A Tool for Subjective and Interactive Visual Data Exploration.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Detecting trends in twitter time series.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Direct Mining of Subjectively Interesting Relational Patterns.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Learning to separate vocals from polyphonic mixtures via ensemble methods and structured output prediction.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Informative data projections: a framework and two examples.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Subjectively interesting alternative clusterings.
Mach. Learn., 2015

Supply and demand of independent UK music artists on the web.
Proceedings of the ACM Web Science Conference, 2015

Interactively Exploring Supply and Demand in the UK Independent Music Scene.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014
Automatic Chord Estimation from Audio: A Review of the State of the Art.
IEEE ACM Trans. Audio Speech Lang. Process., 2014

Interesting pattern mining in multi-relational data.
Data Min. Knowl. Discov., 2014

Mining approximate multi-relational patterns.
Proceedings of the International Conference on Data Science and Advanced Analytics, 2014

2013
Understanding Effects of Subjectivity in Measuring Chord Estimation Accuracy.
IEEE ACM Trans. Audio Speech Lang. Process., 2013

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

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

Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

A Theoretical Framework for Exploratory Data Mining: Recent Insights and Challenges Ahead.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Subjective Interestingness in Exploratory Data Mining.
Proceedings of the Advances in Intelligent Data Analysis XII, 2013

Mining Interesting Patterns in Multi-relational Data with N-ary Relationships.
Proceedings of the Discovery Science - 16th International Conference, 2013

2012
Knowledge discovery interestingness measures based on unexpectedness.
WIREs Data Mining Knowl. Discov., 2012

An intelligent Web agent that autonomously learns how to translate.
Web Intell. Agent Syst., 2012

An End-to-End Machine Learning System for Harmonic Analysis of Music.
IEEE Trans. Speech Audio Process., 2012

The NetCover algorithm for the reconstruction of causal networks.
Neurocomputing, 2012

Learning to Translate: A Statistical and Computational Analysis.
Adv. Artif. Intell., 2012

Using Hyper-genre Training to Explore Genre Information for Automatic Chord Estimation.
Proceedings of the 13th International Society for Music Information Retrieval Conference, 2012

Formalizing Complex Prior Information to Quantify Subjective Interestingness of Frequent Pattern Sets.
Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

An Empirical Comparison of Label Prediction Algorithms on Automatically Inferred Networks.
Proceedings of the ICPRAM 2012, 2012

2011
Maximum entropy models and subjective interestingness: an application to tiles in binary databases.
Data Min. Knowl. Discov., 2011

Meta-song evaluation for chord recognition
CoRR, 2011

NOAM: news outlets analysis and monitoring system.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2011

Celebrity Watch: Browsing News Content by Exploiting Social Intelligence.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Subjectively Interesting Alternative Clusters.
Proceedings of the 2nd MultiClust Workshop: Discovering, 2011

Refining causality: who copied from whom?
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

An information theoretic framework for data mining.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Leveraging Noisy Online Databases for Use in Chord Recognition.
Proceedings of the 12th International Society for Music Information Retrieval Conference, 2011

Mining the Correlation between Lyrical and Audio Features and the Emergence of Mood.
Proceedings of the 12th International Society for Music Information Retrieval Conference, 2011

Interesting Multi-relational Patterns.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Maximum Entropy Modelling for Assessing Results on Real-Valued Data.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Reconstruction of Causal Networks by Set Covering.
Proceedings of the Adaptive and Natural Computing Algorithms, 2011

2010
A framework for mining interesting pattern sets.
SIGKDD Explor., 2010

Automating News Content Analysis: An Application to Gender Bias and Readability.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

An Information-Theoretic Approach to Finding Informative Noisy Tiles in Binary Databases.
Proceedings of the SIAM International Conference on Data Mining, 2010

Detecting Events in a Million New York Times Articles.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Flu Detector - Tracking Epidemics on Twitter.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Finding surprising patterns in textual data streams.
Proceedings of the 2nd International Workshop on Cognitive Information Processing, 2010

2009
Explicit probabilistic models for databases and networks
CoRR, 2009

ModuleDigger: an itemset mining framework for the detection of <i>cis</i>-regulatory modules.
BMC Bioinform., 2009

Found in Translation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Inference and Validation of Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

An Intelligent Agent That Autonomously Learns How to Translate.
Proceedings of the 2009 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2009

Machine Learning with Labeled and Unlabeled Data.
Proceedings of the ESANN 2009, 2009

Learning to translate: a statistical and computational analysis.
Proceedings of the Workshop on Statistical Multilingual Analysis for Retrieval and Translation, 2009

2008
Learning Performance of a Machine Translation System: a Statistical and Computational Analysis.
Proceedings of the Third Workshop on Statistical Machine Translation, 2008

Integrating Microarray and Proteomics Data to Predict the Response of Cetuximab in Patients with Rectal Cancer.
Proceedings of the Biocomputing 2008, 2008

2007
Modeling sequence evolution with kernel methods.
Comput. Optim. Appl., 2007

MINI: Mining Informative Non-redundant Itemsets.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Kernel-based data fusion for gene prioritization.
Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 2007

Learning to Align: A Statistical Approach.
Proceedings of the Advances in Intelligent Data Analysis VII, 2007

A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning.
Proceedings of the ESANN 2007, 2007

Deploying SDP for machine learning.
Proceedings of the ESANN 2007, 2007

Discriminative Sequence Labeling by Z-Score Optimization.
Proceedings of the Machine Learning: ECML 2007, 2007

2006
Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problem.
J. Mach. Learn. Res., 2006

CAFE: a computational tool for the study of gene family evolution.
Bioinform., 2006

The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces.
Proceedings of the Machine Learning: ECML 2006, 2006

Semi-Supervised Learning Using Semi-Definite Programming.
Proceedings of the Semi-Supervised Learning, 2006

2005
Discovering Transcriptional Modules from Motif, Chip-Chip and Microarray Data.
Proceedings of the Biocomputing 2005, 2005

2004
A statistical framework for genomic data fusion.
Bioinform., 2004

Learning from General Label Constraints.
Proceedings of the Structural, 2004

Kernel Methods for Exploratory Pattern Analysis: A Demonstration on Text Data.
Proceedings of the Structural, 2004

2003
Convex Methods for Transduction.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Efficiently Learning the Metric with Side-Information.
Proceedings of the Algorithmic Learning Theory, 14th International Conference, 2003


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