Tijl De Bie - RankMe

224 papers A* 15A 8B 21C 1Misc 3Journal 116Unranked 56

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Untangling Input Language from Reasoning Language: A Diagnostic Framework for Cross-Lingual Moral Alignment in LLMs. CoRR Nan Li, Bo Kang, Tijl De Bie
2026	J	`jnl`	Your Next State-of-the-Art Could Come from Another Domain: A Cross-Domain Analysis of Hierarchical Text Classification. Mach. Learn. Nan Li, Bo Kang, Tijl De Bie
2025	—	`conf`	ABCFair: an Adaptable Benchmark approach for Comparing Fairness methods. EWAF MaryBeth Defrance, Maarten Buyl, Tijl De Bie
2025	J	`jnl`	BiMi Sheets: Infosheets for bias mitigation methods. CoRR MaryBeth Defrance, Guillaume Bied, Maarten Buyl, Jefrey Lijffijt, Tijl De Bie
2025	J	`jnl`	Biased Heritage: How Datasets Shape Models in Facial Expression Recognition. CoRR Iris Dominguez-Catena, Daniel Paternain, Mikel Galar, MaryBeth Defrance, Maarten Buyl, Tijl De Bie
2025	—	`conf`	Building Data-Driven Occupation Taxonomies: A Bottom-Up Multi-Stage Approach via Semantic Clustering and Multi-Agent Collaboration. EMNLP (Industry Track) Nan Li, Bo Kang, Tijl De Bie
2025	J	`jnl`	Building Data-Driven Occupation Taxonomies: A Bottom-Up Multi-Stage Approach via Semantic Clustering and Multi-Agent Collaboration. CoRR Nan Li, Bo Kang, Tijl De Bie
2025	J	`jnl`	Building and Measuring Trust between Large Language Models. CoRR Maarten Buyl, Yousra Fettach, Guillaume Bied, Tijl De Bie
2025	A	`conf`	Content-Agnostic Moderation for Stance-Neutral Recommendations. CIKM Nan Li, Bo Kang, Tijl De Bie
2025	B	`conf`	JobHop: A Large-Scale Dataset of Career Trajectories. IEEE Big Data Iman Johary, Raphaël Romero, Alexandru Cristian Mara, Tijl De Bie
2025	J	`jnl`	JobHop: A Large-Scale Dataset of Career Trajectories. CoRR Iman Johary, Raphaël Romero, Alexandru Mara, Tijl De Bie
2025	J	`jnl`	LLM4Jobs: Unsupervised occupation extraction and standardization leveraging Large Language Models. Knowl. Based Syst. Nan Li, Bo Kang, Tijl De Bie
2025	J	`jnl`	Maximal Combinations of Fairness Definitions. J. Artif. Intell. Res. MaryBeth Defrance, Tijl De Bie
2025	J	`jnl`	Multiresolution Analysis and Statistical Thresholding on Dynamic Networks. CoRR Raphaël Romero, Tijl De Bie, Nick Heard, Alexander Modell
2025	J	`jnl`	SimHawNet: a modified Hawkes process for temporal network simulation. Data Min. Knowl. Discov. Mathilde Perez, Raphaël Romero, Bo Kang, Tijl De Bie, Jefrey Lijffijt, Charlotte Laclau
2025	—	`conf`	What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices. ECML/PKDD (1) Sander Noels, Guillaume Bied, Maarten Buyl, Alexander Rogiers, Yousra Fettach, Jefrey Lijffijt, Tijl De Bie
2025	J	`jnl`	What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices. CoRR Sander Noels, Guillaume Bied, Maarten Buyl, Alexander Rogiers, Yousra Fettach, Jefrey Lijffijt, Tijl De Bie
2024	J	`jnl`	A Challenge-based Survey of E-recruitment Recommendation Systems. ACM Comput. Surv. Yoosof Mashayekhi, Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2024	—	`conf`	A Dutch Financial Large Language Model. ICAIF Sander Noels, Jorne De Blaere, Tijl De Bie
2024	J	`jnl`	A Dutch Financial Large Language Model. CoRR Sander Noels, Jorne De Blaere, Tijl De Bie
2024	A*	`conf`	ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods. NeurIPS MaryBeth Defrance, Maarten Buyl, Tijl De Bie
2024	J	`jnl`	ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods. CoRR MaryBeth Defrance, Maarten Buyl, Tijl De Bie
2024	J	`jnl`	An Empirical Evaluation of Network Representation Learning Methods. Big Data Alexandru Cristian Mara, Jefrey Lijffijt, Tijl De Bie
2024	J	`jnl`	Content-Agnostic Moderation for Stance-Neutral Recommendation. CoRR Nan Li, Bo Kang, Tijl De Bie
2024	J	`jnl`	Evaluating feature attribution methods in the image domain. Mach. Learn. Arne Gevaert, Axel-Jan Rousseau, Thijs Becker, Dirk Valkenborg, Tijl De Bie, Yvan Saeys
2024	J	`jnl`	Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms. CoRR Raphaël Romero, Maarten Buyl, Tijl De Bie, Jefrey Lijffijt
2024	J	`jnl`	FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources. ACM Trans. Intell. Syst. Technol. Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2024	—	`conf`	Fairret: a Flexible Pytorch Library for Fairness. EWAF MaryBeth Defrance, Maarten Buyl, Tijl De Bie
2024	A	`conf`	Fourth Workshop on Recommender Systems for Human Resources (RecSys in HR 2024). RecSys Toine Bogers, David Graus, Mesut Kaya, Chris Johnson, Jens-Joris Decorte, Tijl De Bie
2024	J	`jnl`	GREASE: Graph Imbalance Reduction by Adding Sets of Edges. IEEE Trans. Knowl. Data Eng. Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2024	J	`jnl`	Gaussian Embedding of Temporal Networks. CoRR Raphaël Romero, Jefrey Lijffijt, Riccardo Rastelli, Marco Corneli, Tijl De Bie
2024	J	`jnl`	Incorporating Topological Priors Into Low-Dimensional Visualizations Through Topological Regularization. IEEE Access Edith Heiter, Robin Vandaele, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
2024	J	`jnl`	Inherent Limitations of AI Fairness. Commun. ACM Maarten Buyl, Tijl De Bie
2024	—	`conf`	KamerRaad: Enhancing Information Retrieval in Belgian National Politics Through Hierarchical Summarization and Conversational Interfaces. ECML/PKDD (8) Alexander Rogiers, Maarten Buyl, Bo Kang, Tijl De Bie
2024	J	`jnl`	KamerRaad: Enhancing Information Retrieval in Belgian National Politics through Hierarchical Summarization and Conversational Interfaces. CoRR Alexander Rogiers, Maarten Buyl, Bo Kang, Tijl De Bie
2024	J	`jnl`	Large Language Models Reflect the Ideology of their Creators. CoRR Maarten Buyl, Alexander Rogiers, Sander Noels, Iris Dominguez-Catena, Edith Heiter, Raphaël Romero, Iman Johary, Alexandru Cristian Mara, Jefrey Lijffijt, Tijl De Bie
2024	—	`conf`	Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE. ECML/PKDD (8) Edith Heiter, Liesbet Martens, Ruth Seurinck, Martin Guilliams, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
2024	J	`jnl`	Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE. CoRR Edith Heiter, Liesbet Martens, Ruth Seurinck, Martin Guilliams, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
2024	J	`jnl`	Persuasion with Large Language Models: a Survey. CoRR Alexander Rogiers, Sander Noels, Maarten Buyl, Tijl De Bie
2024	—	`ed.`	Proceedings of the 4th Workshop on Recommender Systems for Human Resources (RecSys-in-HR 2024) co-located with the 18th ACM Conference on Recommender Systems (RecSys 2024), Bari, Italy, 14th-18th October 2024. HR@RECSYS Mesut Kaya, Toine Bogers, David Graus, Chris Johnson, Jens-Joris Decorte, Tijl De Bie
2024	J	`jnl`	Scalable Job Recommendation With Lower Congestion Using Optimal Transport. IEEE Access Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2024	J	`jnl`	TopoLedgerBERT: Topological Learning of Ledger Description Embeddings using Siamese BERT-Networks. CoRR Sander Noels, Sébastien Viaene, Tijl De Bie
2024	J	`jnl`	Your Next State-of-the-Art Could Come from Another Domain: A Cross-Domain Analysis of Hierarchical Text Classification. CoRR Nan Li, Bo Kang, Tijl De Bie
2024	A*	`conf`	fairret: a Framework for Differentiable Fairness Regularization Terms. ICLR Maarten Buyl, MaryBeth Defrance, Tijl De Bie
2023	J	`jnl`	An efficient graph-based peer selection method for financial statements. Intell. Syst. Account. Finance Manag. Sander Noels, Simon De Ridder, Sébastien Viaene, Tijl De Bie
2023	—	`conf`	Automated Financial Analysis Using GPT-4. ECML/PKDD (7) Sander Noels, Adriaan Merlevede, Andrew Fecheyr, Maarten Vanhalst, Nick Meerlaen, Sébastien Viaene, Tijl De Bie
2023	—	`conf`	FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources. HR@RecSys Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2023	J	`jnl`	FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources. CoRR Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2023	J	`jnl`	Gaussian Embedding of Temporal Networks. IEEE Access Raphaël Romero, Jefrey Lijffijt, Riccardo Rastelli, Marco Corneli, Tijl De Bie
2023	J	`jnl`	LLM4Jobs: Unsupervised occupation extraction and standardization leveraging Large Language Models. CoRR Nan Li, Bo Kang, Tijl De Bie
2023	J	`jnl`	Maximal Fairness. CoRR MaryBeth Defrance, Tijl De Bie
2023	—	`conf`	Maximal fairness. FAccT MaryBeth Defrance, Tijl De Bie
2023	J	`jnl`	New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic Graphs. CoRR Raphaël Romero, Tijl De Bie, Jefrey Lijffijt
2023	A	`conf`	ReCon: Reducing Congestion in Job Recommendation using Optimal Transport. RecSys Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2023	J	`jnl`	ReCon: Reducing Congestion in Job Recommendation using Optimal Transport. CoRR Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2023	J	`jnl`	SkillGPT: a RESTful API service for skill extraction and standardization using a Large Language Model. CoRR Nan Li, Bo Kang, Tijl De Bie
2023	J	`jnl`	Topologically Regularized Data Embeddings. CoRR Edith Heiter, Robin Vandaele, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
2023	J	`jnl`	fairret: a Framework for Differentiable Fairness Regularization Terms. CoRR Maarten Buyl, MaryBeth Defrance, Tijl De Bie
2022	—	`conf`	A Systematic Evaluation of Node Embedding Robustness. LoG Alexandru Cristian Mara, Jefrey Lijffijt, Stephan Günnemann, Tijl De Bie
2022	J	`jnl`	A Systematic Evaluation of Node Embedding Robustness. CoRR Alexandru Mara, Jefrey Lijffijt, Stephan Günnemann, Tijl De Bie
2022	J	`jnl`	A challenge-based survey of e-recruitment recommendation systems. CoRR Yoosof Mashayekhi, Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2022	—	`conf`	An Earth Mover's Distance Based Graph Distance Metric For Financial Statements. CIFEr Sander Noels, Benjamin Vandermarliere, Ken Bastiaensen, Tijl De Bie
2022	J	`jnl`	Automating data science. Commun. ACM Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
2022	B	`conf`	Embedding-based next song recommendation for playlists. ESANN Raphaël Romero, Tijl De Bie
2022	J	`jnl`	EvalNE: A framework for network embedding evaluation. SoftwareX Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2022	J	`jnl`	Evaluating Feature Attribution Methods in the Image Domain. CoRR Arne Gevaert, Axel-Jan Rousseau, Thijs Becker, Dirk Valkenborg, Tijl De Bie, Yvan Saeys
2022	J	`jnl`	Evaluating Representation Learning and Graph Layout Methods for Visualization. IEEE Computer Graphics and Applications Edith Heiter, Bo Kang, Tijl De Bie, Jefrey Lijffijt
2022	J	`jnl`	Graph-Survival: A Survival Analysis Framework for Machine Learning on Temporal Networks. CoRR Raphaël Romero, Bo Kang, Tijl De Bie
2022	J	`jnl`	Inherent Limitations of AI Fairness. CoRR Maarten Buyl, Tijl De Bie
2022	—	`conf`	Mining Interesting Outlier Subgraphs in Attributed Graphs. KI (Workshops) Ahmad Mel, Tijl De Bie
2022	J	`jnl`	Optimal Transport of Binary Classifiers to Fairness. CoRR Maarten Buyl, Tijl De Bie
2022	A*	`conf`	Optimal Transport of Classifiers to Fairness. NeurIPS Maarten Buyl, Tijl De Bie
2022	A	`conf`	The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data? AISTATS Robin Vandaele, Bo Kang, Tijl De Bie, Yvan Saeys
2022	A*	`conf`	Topologically Regularized Data Embeddings. ICLR Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys
2021	—	`conf`	Adversarial Robustness of Probabilistic Network Embedding for Link Prediction. PKDD/ECML Workshops (2) Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021	J	`jnl`	Adversarial Robustness of Probabilistic Network Embedding for Link Prediction. CoRR Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021	J	`jnl`	An Earth Mover's Distance Based Graph Distance Metric For Financial Statements. CoRR Sander Noels, Benjamin Vandermarliere, Ken Bastiaensen, Tijl De Bie
2021	J	`jnl`	Automating Data Science: Prospects and Challenges. CoRR Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
2021	B	`conf`	Conditional t-SNE: More informative t-SNE embeddings. DSAA Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2021	J	`jnl`	Conditional t-SNE: more informative t-SNE embeddings. Mach. Learn. Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2021	—	`conf`	Explanations for Network Embedding-Based Link Predictions. PKDD/ECML Workshops (1) Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021	J	`jnl`	Mining explainable local and global subgraph patterns with surprising densities. Data Min. Knowl. Discov. Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021	—	`conf`	Quantifying and Reducing Imbalance in Networks. HR@RecSys Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021	J	`jnl`	Stable topological signatures for metric trees through graph approximations. Pattern Recognit. Lett. Robin Vandaele, Bastian Rieck, Yvan Saeys, Tijl De Bie
2021	J	`jnl`	The Curse Revisited: a Newly Quantified Concept of Meaningful Distances for Learning from High-Dimensional Noisy Data. CoRR Robin Vandaele, Bo Kang, Tijl De Bie, Yvan Saeys
2021	—	`conf`	The KL-Divergence Between a Graph Model and its Fair I-Projection as a Fairness Regularizer. ECML/PKDD (2) Maarten Buyl, Tijl De Bie
2021	J	`jnl`	The KL-Divergence between a Graph Model and its Fair I-Projection as a Fairness Regularizer. CoRR Maarten Buyl, Tijl De Bie
2021	J	`jnl`	Topologically Regularized Data Embeddings. CoRR Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys
2020	J	`jnl`	A Constrained Randomization Approach to Interactive Visual Data Exploration with Subjective Feedback. IEEE Trans. Knowl. Data Eng. Bo Kang, Kai Puolamäki, Jefrey Lijffijt, Tijl De Bie
2020	J	`jnl`	ALPINE: Active Link Prediction using Network Embedding. CoRR Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020	B	`conf`	Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress? DSAA Alexandru Cristian Mara, Jefrey Lijffijt, Tijl De Bie
2020	B	`conf`	Block-Approximated Exponential Random Graphs. DSAA Florian Adriaens, Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2020	A	`conf`	CSNE: Conditional Signed Network Embedding. CIKM Alexandru Mara, Yoosof Mashayekhi, Jefrey Lijffijt, Tijl De Bie
2020	J	`jnl`	CSNE: Conditional Signed Network Embedding. CoRR Alexandru Mara, Yoosof Mashayekhi, Jefrey Lijffijt, Tijl De Bie
2020	A*	`conf`	DeBayes: a Bayesian Method for Debiasing Network Embeddings. ICML Maarten Buyl, Tijl De Bie
2020	J	`jnl`	DeBayes: a Bayesian method for debiasing network embeddings. CoRR Maarten Buyl, Tijl De Bie
2020	A	`conf`	Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach. SDM Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020	J	`jnl`	Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach. CoRR Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020	C	`conf`	FACE: Feasible and Actionable Counterfactual Explanations. AIES Rafael Poyiadzi, Kacper Sokol, Raúl Santos-Rodríguez, Tijl De Bie, Peter A. Flach
2020	J	`jnl`	FONDUE: A Framework for Node Disambiguation Using Network Embeddings. CoRR Ahmad Mel, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020	B	`conf`	FONDUE: Framework for Node Disambiguation Using Network Embeddings. DSAA Ahmad Mel, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020	B	`conf`	Gibbs Sampling Subjectively Interesting Tiles. IDA Anes Bendimerad, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2020	B	`conf`	Graph Approximations to Geodesics on Metric Graphs. ICPR Robin Vandaele, Yvan Saeys, Tijl De Bie
2020	J	`jnl`	Interactive visual data exploration with subjective feedback: an information-theoretic approach. Data Min. Knowl. Discov. Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020	J	`jnl`	Mining Topological Structure in Graphs through Forest Representations. J. Mach. Learn. Res. Robin Vandaele, Yvan Saeys, Tijl De Bie
2020	J	`jnl`	Network Representation Learning for Link Prediction: Are we improving upon simple heuristics? CoRR Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2020	J	`jnl`	Relaxing the strong triadic closure problem for edge strength inference. Data Min. Knowl. Discov. Florian Adriaens, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt, Antonis Matakos, Polina Rozenshtein
2020	J	`jnl`	SIAS-miner: mining subjectively interesting attributed subgraphs. Data Min. Knowl. Discov. Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2020	J	`jnl`	Scalable Dyadic Independence Models with Local and Global Constraints. CoRR Florian Adriaens, Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2019	—	`conf`	Conditional Network Embeddings. BNAIC/BENELEARN Bo Kang, Jefrey Lijffijt, Tijl De Bie
2019	—	`conf`	Conditional Network Embeddings. ICLR (Poster) Bo Kang, Jefrey Lijffijt, Tijl De Bie
2019	J	`jnl`	Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information. CoRR Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2019	A*	`conf`	Contrastive Antichains in Hierarchies. KDD Anes Bendimerad, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2019	J	`jnl`	Design and validation of an auditory biofeedback system for modification of running parameters. J. Multimodal User Interfaces Valerio Lorenzoni, Pieter Van den Berghe, Pieter-Jan Maes, Tijl De Bie, Dirk De Clercq, Marc Leman
2019	A	`conf`	Discovering Interesting Cycles in Directed Graphs. CIKM Florian Adriaens, Çigdem Aslay, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt
2019	J	`jnl`	Discovering Interesting Cycles in Directed Graphs. CoRR Florian Adriaens, Çigdem Aslay, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt
2019	—	`conf`	EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction. RML@ICLR Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2019	—	`conf`	EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction. EDML@SDM Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2019	J	`jnl`	EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction. CoRR Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2019	J	`jnl`	ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions. CoRR Bo Kang, Jefrey Lijffijt, Tijl De Bie
2019	J	`jnl`	FACE: Feasible and Actionable Counterfactual Explanations. CoRR Rafael Poyiadzi, Kacper Sokol, Raúl Santos-Rodriguez, Tijl De Bie, Peter A. Flach
2019	J	`jnl`	Mining Subjectively Interesting Attributed Subgraphs. CoRR Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2019	J	`jnl`	Opinion Dynamics with Backfire Effect and Biased Assimilation. CoRR Xi Chen, Panayiotis Tsaparas, Jefrey Lijffijt, Tijl De Bie
2019	J	`jnl`	SIMIT: Subjectively Interesting Motifs in Time Series. Entropy Junning Deng, Jefrey Lijffijt, Bo Kang, Tijl De Bie
2019	J	`jnl`	Subjectively interesting connecting trees and forests. Data Min. Knowl. Discov. Florian Adriaens, Jefrey Lijffijt, Tijl De Bie
2018	—	`conf`	A biofeedback music-sonification system for gait retraining. MOCO Valerio Lorenzoni, Pieter-Jan Maes, Pieter Van den Berghe, Dirk De Clercq, Tijl De Bie, Marc Leman
2018	J	`jnl`	Automating Data Science (Dagstuhl Seminar 18401). Dagstuhl Reports Tijl De Bie, Luc De Raedt, Holger H. Hoos, Padhraic Smyth
2018	J	`jnl`	Conditional Network Embeddings. CoRR Bo Kang, Jefrey Lijffijt, Tijl De Bie
2018	J	`jnl`	From acquaintance to best friend forever: robust and fine-grained inference of social tie strengths. CoRR Florian Adriaens, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt, Polina Rozenshtein
2018	J	`jnl`	From raw audio to a seamless mix: creating an automated DJ system for Drum and Bass. EURASIP J. Audio Speech Music. Process. Len Vande Veire, Tijl De Bie
2018	A*	`conf`	Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach. ICDE Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2018	—	`conf`	Local Topological Data Analysis to Uncover the Global Structure of Data Approaching Graph-Structured Topologies. ECML/PKDD (2) Robin Vandaele, Tijl De Bie, Yvan Saeys
2018	—	`conf`	Ordinal Label Proportions. ECML/PKDD (1) Rafael Poyiadzi, Raúl Santos-Rodríguez, Tijl De Bie
2018	A*	`conf`	Quantifying and Minimizing Risk of Conflict in Social Networks. KDD Xi Chen, Jefrey Lijffijt, Tijl De Bie
2018	J	`jnl`	SICA: subjectively interesting component analysis. Data Min. Knowl. Discov. Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2018	A*	`conf`	Subjectively Interesting Subgroup Discovery on Real-Valued Targets. ICDE Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie
2017	B	`conf`	Hierarchical Novelty Detection. IDA Paolo Simeone, Raúl Santos-Rodríguez, Matt McVicar, Jefrey Lijffijt, Tijl De Bie
2017	J	`jnl`	Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach. CoRR Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2017	—	`conf`	Subjectively Interesting Connecting Trees. ECML/PKDD (2) Florian Adriaens, Jefrey Lijffijt, Tijl De Bie
2017	J	`jnl`	Subjectively Interesting Subgroup Discovery on Real-valued Targets. CoRR Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie
2016	—	`conf`	A Tool for Subjective and Interactive Visual Data Exploration. ECML/PKDD (3) Bo Kang, Kai Puolamäki, Jefrey Lijffijt, Tijl De Bie
2016	—	`conf`	Detecting trends in twitter time series. MLSP Tijl De Bie, Jefrey Lijffijt, Cédric Mesnage, Raúl Santos-Rodriguez
2016	A*	`conf`	Direct Mining of Subjectively Interesting Relational Patterns. ICDM Tias Guns, Achille Aknin, Jefrey Lijffijt, Tijl De Bie
2016	B	`conf`	Informative data projections: a framework and two examples. ESANN Tijl De Bie, Jefrey Lijffijt, Raúl Santos-Rodríguez, Bo Kang
2016	—	`conf`	Interactive Visual Data Exploration with Subjective Feedback. ECML/PKDD (2) Kai Puolamäki, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2016	Misc	`conf`	Learning to separate vocals from polyphonic mixtures via ensemble methods and structured output prediction. ICASSP Matt McVicar, Raúl Santos-Rodriguez, Tijl De Bie
2016	J	`jnl`	P-N-RMiner: a generic framework for mining interesting structured relational patterns. Int. J. Data Sci. Anal. Jefrey Lijffijt, Eirini Spyropoulou, Bo Kang, Tijl De Bie
2016	J	`jnl`	SuMoTED: An intuitive edit distance between rooted unordered uniquely-labelled trees. Pattern Recognit. Lett. Matt McVicar, Benjamin Sach, Cédric Mesnage, Jefrey Lijffijt, Eirini Spyropoulou, Tijl De Bie
2016	J	`jnl`	Subjective interestingness of subgraph patterns. Mach. Learn. Matthijs van Leeuwen, Tijl De Bie, Eirini Spyropoulou, Cédric Mesnage
2016	A*	`conf`	Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations. KDD Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodriguez, Tijl De Bie
2015	B	`ed.`	Advances in Intelligent Data Analysis XIV - 14th International Symposium, IDA 2015, Saint Etienne, France, October 22-24, 2015, Proceedings IDA Élisa Fromont, Tijl De Bie, Matthijs van Leeuwen
2015	J	`jnl`	Informative Data Projections: A Framework and Two Examples. CoRR Tijl De Bie, Jefrey Lijffijt, Raúl Santos-Rodriguez, Bo Kang
2015	—	`conf`	Interactively Exploring Supply and Demand in the UK Independent Music Scene. ECML/PKDD (3) Matt McVicar, Cédric Mesnage, Jefrey Lijffijt, Tijl De Bie
2015	B	`conf`	P-N-RMiner: A generic framework for mining interesting structured relational patterns. DSAA Jefrey Lijffijt, Eirini Spyropoulou, Bo Kang, Tijl De Bie
2015	J	`jnl`	Subjectively interesting alternative clusterings. Mach. Learn. Kleanthis-Nikolaos Kontonasios, Tijl De Bie
2015	—	`conf`	Supply and demand of independent UK music artists on the web. WebSci Matt McVicar, Cédric Mesnage, Jefrey Lijffijt, Eirini Spyropoulou, Tijl De Bie
2014	J	`jnl`	Automatic Chord Estimation from Audio: A Review of the State of the Art. IEEE ACM Trans. Audio Speech Lang. Process. Matt McVicar, Raúl Santos-Rodriguez, Yizhao Ni, Tijl De Bie
2014	J	`jnl`	Interesting pattern mining in multi-relational data. Data Min. Knowl. Discov. Eirini Spyropoulou, Tijl De Bie, Mario Boley
2014	B	`conf`	Mining approximate multi-relational patterns. DSAA Eirini Spyropoulou, Tijl De Bie
2013	—	`conf`	A Theoretical Framework for Exploratory Data Mining: Recent Insights and Challenges Ahead. ECML/PKDD (3) Tijl De Bie, Eirini Spyropoulou
2013	J	`jnl`	Guest editors' introduction: special issue of selected papers from ECML-PKDD 2012. Mach. Learn. Tijl De Bie, Peter A. Flach
2013	J	`jnl`	Guest editors' introduction: special section of selected papers from ECML-PKDD 2012. Data Min. Knowl. Discov. Tijl De Bie, Peter A. Flach
2013	—	`conf`	Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data. ECML/PKDD (2) Kleanthis-Nikolaos Kontonasios, Jilles Vreeken, Tijl De Bie
2013	B	`conf`	Mining Interesting Patterns in Multi-relational Data with N-ary Relationships. Discovery Science Eirini Spyropoulou, Tijl De Bie, Mario Boley
2013	B	`conf`	Subjective Interestingness in Exploratory Data Mining. IDA Tijl De Bie
2013	J	`jnl`	Understanding Effects of Subjectivity in Measuring Chord Estimation Accuracy. IEEE ACM Trans. Audio Speech Lang. Process. Yizhao Ni, Matt McVicar, Raúl Santos-Rodríguez, Tijl De Bie
2012	—	`conf`	An Empirical Comparison of Label Prediction Algorithms on Automatically Inferred Networks. ICPRAM (2) Omar Ali, Giovanni Zappella, Tijl De Bie, Nello Cristianini
2012	J	`jnl`	An End-to-End Machine Learning System for Harmonic Analysis of Music. IEEE Trans. Speech Audio Process. Yizhao Ni, Matt McVicar, Raúl Santos-Rodriguez, Tijl De Bie
2012	J	`jnl`	An intelligent Web agent that autonomously learns how to translate. Web Intell. Agent Syst. Marco Turchi, Tijl De Bie, Nello Cristianini
2012	B	`conf`	Formalizing Complex Prior Information to Quantify Subjective Interestingness of Frequent Pattern Sets. IDA Kleanthis-Nikolaos Kontonasios, Tijl De Bie
2012	J	`jnl`	Knowledge discovery interestingness measures based on unexpectedness. WIREs Data Mining Knowl. Discov. Kleanthis-Nikolaos Kontonasios, Eirini Spyropoulou, Tijl De Bie
2012	J	`jnl`	Learning to Translate: A Statistical and Computational Analysis. Adv. Artif. Intell. Marco Turchi, Tijl De Bie, Cyril Goutte, Nello Cristianini
2012	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part I ECML/PKDD (1) Peter A. Flach, Tijl De Bie, Nello Cristianini
2012	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II ECML/PKDD (2) Peter A. Flach, Tijl De Bie, Nello Cristianini
2012	J	`jnl`	The NetCover algorithm for the reconstruction of causal networks. Neurocomputing Nick Fyson, Tijl De Bie, Nello Cristianini
2012	—	`conf`	Using Hyper-genre Training to Explore Genre Information for Automatic Chord Estimation. ISMIR Yizhao Ni, Matt McVicar, Raúl Santos-Rodriguez, Tijl De Bie
2011	J	`jnl`	An end-to-end machine learning system for harmonic analysis of music CoRR Yizhao Ni, Matt McVicar, Raúl Santos-Rodriguez, Tijl De Bie
2011	A*	`conf`	An information theoretic framework for data mining. KDD Tijl De Bie
2011	—	`conf`	Celebrity Watch: Browsing News Content by Exploiting Social Intelligence. ECML/PKDD (3) Omar Ali, Ilias N. Flaounas, Tijl De Bie, Nello Cristianini
2011	J	`jnl`	Interesting Multi-Relational Patterns CoRR Eirini Spyropoulou, Tijl De Bie
2011	A*	`conf`	Interesting Multi-relational Patterns. ICDM Eirini Spyropoulou, Tijl De Bie
2011	—	`conf`	Leveraging Noisy Online Databases for Use in Chord Recognition. ISMIR Matt McVicar, Yizhao Ni, Tijl De Bie, Raúl Santos-Rodriguez
2011	A*	`conf`	Maximum Entropy Modelling for Assessing Results on Real-Valued Data. ICDM Kleanthis-Nikolaos Kontonasios, Jilles Vreeken, Tijl De Bie
2011	J	`jnl`	Maximum entropy models and subjective interestingness: an application to tiles in binary databases. Data Min. Knowl. Discov. Tijl De Bie
2011	J	`jnl`	Meta-song evaluation for chord recognition CoRR Yizhao Ni, Matt McVicar, Raúl Santos-Rodriguez, Tijl De Bie
2011	—	`conf`	Mining the Correlation between Lyrical and Audio Features and the Emergence of Mood. ISMIR Matt McVicar, Tim Freeman, Tijl De Bie
2011	—	`conf`	NOAM: news outlets analysis and monitoring system. SIGMOD Conference Ilias N. Flaounas, Omar Ali, Marco Turchi, Tristan Snowsill, Florent Nicart, Tijl De Bie, Nello Cristianini
2011	—	`conf`	Reconstruction of Causal Networks by Set Covering. ICANNGA (2) Nick Fyson, Tijl De Bie, Nello Cristianini
2011	A*	`conf`	Refining causality: who copied from whom? KDD Tristan Mark Snowsill, Nick Fyson, Tijl De Bie, Nello Cristianini
2011	—	`conf`	Subjectively Interesting Alternative Clusters. MultiClust@ECML/PKDD Tijl De Bie
2010	J	`jnl`	A framework for mining interesting pattern sets. SIGKDD Explor. Tijl De Bie, Kleanthis-Nikolaos Kontonasios, Eirini Spyropoulou
2010	A	`conf`	An Information-Theoretic Approach to Finding Informative Noisy Tiles in Binary Databases. SDM Kleanthis-Nikolaos Kontonasios, Tijl De Bie
2010	—	`conf`	Automating News Content Analysis: An Application to Gender Bias and Readability. WAPA Omar Ali, Ilias N. Flaounas, Tijl De Bie, Nick Mosdell, Justin Lewis, Nello Cristianini
2010	—	`conf`	Detecting Events in a Million New York Times Articles. ECML/PKDD (3) Tristan Snowsill, Ilias N. Flaounas, Tijl De Bie, Nello Cristianini
2010	—	`conf`	Finding surprising patterns in textual data streams. CIP Tristan Snowsill, Florent Nicart, Marco Stefani, Tijl De Bie, Nello Cristianini
2010	—	`conf`	Flu Detector - Tracking Epidemics on Twitter. ECML/PKDD (3) Vasileios Lampos, Tijl De Bie, Nello Cristianini
2010	J	`jnl`	Maximum entropy models and subjective interestingness: an application to tiles in binary databases CoRR Tijl De Bie
2010	J	`jnl`	Reconstruction of Causal Networks by Set Covering CoRR Nick Fyson, Tijl De Bie, Nello Cristianini
2009	—	`conf`	An Intelligent Agent That Autonomously Learns How to Translate. IAT Marco Turchi, Tijl De Bie, Nello Cristianini
2009	J	`jnl`	Explicit probabilistic models for databases and networks CoRR Tijl De Bie
2009	—	`conf`	Found in Translation. ECML/PKDD (2) Marco Turchi, Ilias N. Flaounas, Omar Ali, Tijl De Bie, Tristan Snowsill, Nello Cristianini
2009	—	`conf`	Inference and Validation of Networks. ECML/PKDD (1) Ilias N. Flaounas, Marco Turchi, Tijl De Bie, Nello Cristianini
2009	—	`conf`	Learning to translate: a statistical and computational analysis. SMART@EAMT Marco Turchi, Tijl De Bie, Nello Cristianini
2009	B	`conf`	Machine Learning with Labeled and Unlabeled Data. ESANN Tijl De Bie, Thiago Turchetti Maia, Antônio de Pádua Braga
2009	J	`jnl`	ModuleDigger: an itemset mining framework for the detection of BMC Bioinform. Hong Sun, Tijl De Bie, Valerie Storms, Qiang Fu, Thomas Dhollander, Karen Lemmens, Annemieke Verstuyf, Bart De Moor, Kathleen Marchal
2008	Misc	`conf`	Integrating Microarray and Proteomics Data to Predict the Response of Cetuximab in Patients with Rectal Cancer. Pacific Symposium on Biocomputing Anneleen Daemen, Olivier Gevaert, Tijl De Bie, Annelies Debucquoy, Jean-Pascal Machiels, Bart De Moor, Karin Haustermans
2008	—	`conf`	Learning Performance of a Machine Translation System: a Statistical and Computational Analysis. WMT@ACL Marco Turchi, Tijl De Bie, Nello Cristianini
2007	B	`conf`	A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning. ESANN Sándor Szedmák, Tijl De Bie, David R. Hardoon
2007	B	`conf`	Deploying SDP for machine learning. ESANN Tijl De Bie
2007	—	`conf`	Discriminative Sequence Labeling by Z-Score Optimization. ECML Elisa Ricci, Tijl De Bie, Nello Cristianini
2007	—	`conf`	Kernel-based data fusion for gene prioritization. ISMB/ECCB (Supplement of Bioinformatics) Tijl De Bie, Léon-Charles Tranchevent, Liesbeth M. M. van Oeffelen, Yves Moreau
2007	B	`conf`	Learning to Align: A Statistical Approach. IDA Elisa Ricci, Tijl De Bie, Nello Cristianini
2007	—	`conf`	MINI: Mining Informative Non-redundant Itemsets. PKDD Arianna Gallo, Tijl De Bie, Nello Cristianini
2007	J	`jnl`	Modeling sequence evolution with kernel methods. Comput. Optim. Appl. Margherita Bresco, Marco Turchi, Tijl De Bie, Nello Cristianini
2006	J	`jnl`	CAFE: a computational tool for the study of gene family evolution. Bioinform. Tijl De Bie, Nello Cristianini, Jeffery P. Demuth, Matthew W. Hahn
2006	J	`jnl`	Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problem. J. Mach. Learn. Res. Tijl De Bie, Nello Cristianini
2006	—	`ch.`	Semi-Supervised Learning Using Semi-Definite Programming. Semi-Supervised Learning Tijl De Bie, Nello Cristianini
2006	—	`conf`	The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces. ECML Alexander N. Dolia, Tijl De Bie, Christopher J. Harris, John Shawe-Taylor, D. M. Titterington
2005	Misc	`conf`	Discovering Transcriptional Modules from Motif, Chip-Chip and Microarray Data. Pacific Symposium on Biocomputing Tijl De Bie, Patrick Monsieurs, Kristof Engelen, Bart De Moor, Nello Cristianini, Kathleen Marchal
2004	J	`jnl`	A statistical framework for genomic data fusion. Bioinform. Gert R. G. Lanckriet, Tijl De Bie, Nello Cristianini, Michael I. Jordan, William Stafford Noble
2004	—	`conf`	Kernel Methods for Exploratory Pattern Analysis: A Demonstration on Text Data. SSPR/SPR Tijl De Bie, Nello Cristianini
2004	—	`conf`	Learning from General Label Constraints. SSPR/SPR Tijl De Bie, Johan A. K. Suykens, Bart De Moor
2003	—	`conf`	Convex Methods for Transduction. NIPS Tijl De Bie, Nello Cristianini
2003	B	`conf`	Efficiently Learning the Metric with Side-Information. ALT Tijl De Bie, Michinari Momma, Nello Cristianini