Henrik Boström

188 papers A* 8A 4B 22C 16Misc 4Journal 47Unranked 83

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Kinetic-Energy Perspective of Flow Matching. CoRR Ziyun Li, Huancheng Hu, Soon Hoe Lim, Xuyu Li, Fei Gao, Enmao Diao, Zezhen Ding, Michalis Vazirgiannis, Henrik Boström
2026	—	`conf`	An Investigation of Conformal Test Martingales. The Importance of Being Learnable Henrik Boström
2025	A*	`conf`	CADQ: Attribute-Consistent Face Cartoonization with Cross-modal Aligned and Deformable Quantization. ACM Multimedia Yongjie Hu, Yifan Jiang, Ziyun Li, Fei Gao, Henrik Boström, Nannan Wang
2025	J	`jnl`	ConANN: Conformal Approximate Nearest Neighbor Search. Proc. VLDB Endow. Sonia Horchidan, Fabian Zeiher, Henrik Boström, Paris Carbone
2025	—	`conf`	Detect Adversarial Examples with Exchangeability Martingale. COPA Genghua Dong, Roman Bresson, Henrik Boström
2025	J	`jnl`	EnfoPath: Energy-Informed Analysis of Generative Trajectories in Flow Matching. CoRR Ziyun Li, Ben Dai, Huancheng Hu, Henrik Boström, Soon Hoe Lim
2025	B	`conf`	Explaining Deep Neural Networks with Example and Pixel Attribution. DS Genghua Dong, Henrik Boström, Roman Bresson, Amr Alkhatib
2025	Misc	`conf`	Explaining Representations in Correlation-based Deep Multiview Representation Learning. ICASSP Maurice Kuschel, Amr Alkhatib, Tanuj Hasija, Henrik Boström
2025	—	`conf`	FlowGuard: Guarding Flow Matching via Conformal Sampling. COPA Ziyun Li, Henrik Boström
2025	—	`ed.`	Fourteenth Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2025, 10-12 September 2025, London, UK. COPA Khuong An Nguyen, Zhiyuan Luo, Harris Papadopoulos, Tuwe Löfström, Lars Carlsson, Henrik Boström
2025	B	`conf`	Obtaining Example-Based Explanations from Deep Neural Networks. IDA Genghua Dong, Henrik Boström, Michalis Vazirgiannis, Roman Bresson
2025	J	`jnl`	Obtaining Example-Based Explanations from Deep Neural Networks. CoRR Genghua Dong, Henrik Boström, Michalis Vazirgiannis, Roman Bresson
2025	A*	`conf`	Prediction via Shapley Value Regression. ICML Amr Alkhatib, Roman Bresson, Henrik Boström, Michalis Vazirgiannis
2025	J	`jnl`	Prediction via Shapley Value Regression. CoRR Amr Alkhatib, Roman Bresson, Henrik Boström, Michalis Vazirgiannis
2025	—	`conf`	Preface. COPA Harris Papadopoulos, Khuong An Nguyen, Zhiyuan Luo, Tuwe Löfström, Lars Carlsson, Henrik Boström
2025	—	`conf`	Testing Exchangeability for Multiple Sequences of P-values. COPA Henrik Boström
2024	A*	`conf`	A Simple and Yet Fairly Effective Defense for Graph Neural Networks. AAAI Sofiane Ennadir, Yassine Abbahaddou, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström
2024	J	`jnl`	A Simple and Yet Fairly Effective Defense for Graph Neural Networks. CoRR Sofiane Ennadir, Yassine Abbahaddou, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström
2024	A*	`conf`	Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks. ICLR Yassine Abbahaddou, Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström
2024	J	`jnl`	Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks. CoRR Yassine Abbahaddou, Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström
2024	J	`jnl`	Can local explanation techniques explain linear additive models? Data Min. Knowl. Discov. Amir Hossein Akhavan Rahnama, Judith Bütepage, Pierre Geurts, Henrik Boström
2024	—	`conf`	CoPAL: Conformal Prediction in Active Learning An Algorithm for Enhancing Remaining Useful Life Estimation in Predictive Maintenance. COPA Zahra Kharazian, Tony Lindgren, Sindri Magnússon, Henrik Boström
2024	—	`conf`	Conformal Prediction in Python with crepes. COPA Henrik Boström
2024	—	`conf`	Conformal Regression with Reject Option. COPA Ulf Johansson, Cecilia Sönströd, Henrik Boström
2024	—	`conf`	Estimating Quality of Approximated Shapley Values Using Conformal Prediction. COPA Amr Alkhatib, Henrik Boström, Ulf Johansson
2024	—	`conf`	Example-Based Explanations of Random Forest Predictions. IDA (2) Henrik Boström
2024	J	`jnl`	Explaining Predictions by Characteristic Rules. CoRR Amr Alkhatib, Henrik Boström, Michalis Vazirgiannis
2024	—	`conf`	Faithfulness of Local Explanations for Tree-Based Ensemble Models. DS (2) Amir Hossein Akhavan Rahnama, Pierre Geurts, Henrik Boström
2024	—	`conf`	Fast Approximation of Shapley Values with Limited Data. SCAI Amr Alkhatib, Henrik Boström
2024	J	`jnl`	Generating graph perturbations to enhance the generalization of GNNs. AI Open Sofiane Ennadir, Giannis Nikolentzos, Michalis Vazirgiannis, Henrik Boström
2024	—	`conf`	Interpretable Graph Neural Networks for Heterogeneous Tabular Data. DS (1) Amr Alkhatib, Henrik Boström
2024	J	`jnl`	Interpretable Graph Neural Networks for Heterogeneous Tabular Data. CoRR Amr Alkhatib, Henrik Boström
2024	A	`conf`	Interpretable Graph Neural Networks for Tabular Data. ECAI Amr Alkhatib, Sofiane Ennadir, Henrik Boström, Michalis Vazirgiannis
2024	—	`conf`	Local List-Wise Explanations of LambdaMART. xAI (2) Amir Hossein Akhavan Rahnama, Judith Bütepage, Henrik Boström
2024	—	`conf`	Local Point-wise Explanations of LambdaMART. SCAI Amir Hossein Akhavan Rahnama, Judith Bütepage, Henrik Boström
2024	—	`ed.`	The 13th Symposium on Conformal and Probabilistic Prediction with Applications, 9-11 September 2024, Politecnico di Milano, Milano, Italy. COPA Simone Vantini, Matteo Fontana, Aldo Solari, Henrik Boström, Lars Carlsson
2023	—	`conf`	Approximating Score-based Explanation Techniques Using Conformal Regression. COPA Amr Alkhatib, Henrik Boström, Sofiane Ennadir, Ulf Johansson
2023	J	`jnl`	Approximating Score-based Explanation Techniques Using Conformal Regression. CoRR Amr Alkhatib, Henrik Boström, Sofiane Ennadir, Ulf Johansson
2023	—	`conf`	Confidence Classifiers with Guaranteed Accuracy or Precision. COPA Ulf Johansson, Cecilia Sönströd, Tuwe Löfström, Henrik Boström
2023	—	`ed.`	Conformal and Probabilistic Prediction with Applications, 13-15 September 2023, Limassol, Cyprus. COPA Harris Papadopoulos, Khuong An Nguyen, Henrik Boström, Lars Carlsson
2023	—	`conf`	Conformalized Adversarial Attack Detection for Graph Neural Networks. COPA Sofiane Ennadir, Amr Alkhatib, Henrik Boström, Michalis Vazirgiannis
2023	J	`jnl`	Example-Based Explanations of Random Forest Predictions. CoRR Henrik Boström
2023	J	`jnl`	Interpretable Graph Neural Networks for Tabular Data. CoRR Amr Alkhatib, Sofiane Ennadir, Henrik Boström, Michalis Vazirgiannis
2023	—	`conf`	Investigating the Contribution of Privileged Information in Knowledge Transfer LUPI by Explainable Machine Learning. COPA Niharika Gauraha, Henrik Boström
2023	—	`conf`	Mondrian Predictive Systems for Censored Data. COPA Henrik Boström, Henrik Linusson, Anders Vesterberg
2023	—	`conf`	Tutorial on using Conformal Predictive Systems in KNIME. COPA Tuwe Löfström, Alexander Bondaletov, Artem Ryasik, Henrik Boström, Ulf Johansson
2023	—	`conf`	UnboundAttack: Generating Unbounded Adversarial Attacks to Graph Neural Networks. COMPLEX NETWORKS (1) Sofiane Ennadir, Amr Alkhatib, Giannis Nikolentzos, Michalis Vazirgiannis, Henrik Boström
2022	—	`conf`	Assessing Explanation Quality by Venn Prediction. COPA Amr Alkhatib, Henrik Boström, Ulf Johansson
2022	—	`ed.`	Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK COPA Ulf Johansson, Henrik Boström, Khuong An Nguyen, Zhiyuan Luo, Lars Carlsson
2022	—	`conf`	Explaining Predictions by Characteristic Rules. ECML/PKDD (1) Amr Alkhatib, Henrik Boström, Michalis Vazirgiannis
2022	J	`jnl`	Image Keypoint Matching using Graph Neural Networks. CoRR Nancy Xu, Giannis Nikolentzos, Michalis Vazirgiannis, Henrik Boström
2022	—	`conf`	Preface. COPA Ulf Johansson, Henrik Boström, Khuong An Nguyen, Zhiyuan Luo, Lars Carlsson
2022	J	`jnl`	Random subspace and random projection nearest neighbor ensembles for high dimensional data. Expert Syst. Appl. Sampath Deegalla, Keerthi Walgama, Panagiotis Papapetrou, Henrik Boström
2022	J	`jnl`	Rule extraction with guarantees from regression models. Pattern Recognit. Ulf Johansson, Cecilia Sönströd, Tuwe Löfström, Henrik Boström
2022	—	`conf`	crepes: a Python Package for Generating Conformal Regressors and Predictive Systems. COPA Henrik Boström
2021	—	`conf`	Calibrating multi-class models. COPA Ulf Johansson, Tuwe Löfström, Henrik Boström
2021	J	`jnl`	Evaluation of Local Model-Agnostic Explanations Using Ground Truth. CoRR Amir Hossein Akhavan Rahnama, Judith Bütepage, Pierre Geurts, Henrik Boström
2021	—	`conf`	Evaluation of updating strategies for conformal predictive systems in the presence of extreme events. COPA Hugo Werner, Lars Carlsson, Ernst Ahlberg, Henrik Boström
2021	—	`conf`	Image Keypoint Matching Using Graph Neural Networks. COMPLEX NETWORKS Nancy Xu, Giannis Nikolentzos, Michalis Vazirgiannis, Henrik Boström
2021	—	`conf`	Investigating Normalized Conformal Regressors. SSCI Ulf Johansson, Henrik Boström, Tuwe Löfström
2021	—	`conf`	Mondrian conformal predictive distributions. COPA Henrik Boström, Ulf Johansson, Tuwe Löfström
2021	J	`jnl`	Towards interpretability of Mixtures of Hidden Markov Models. CoRR Negar Safinianaini, Henrik Boström
2021	B	`conf`	Well-Calibrated and Sharp Interpretable Multi-Class Models. MDAI Ulf Johansson, Tuwe Löfström, Henrik Boström
2020	—	`conf`	Classication of aerosol particles using inductive conformal prediction. COPA Linn Karlsson, Henrik Boström, Paul Zieger
2020	J	`jnl`	Corrigendum to 'Learning from heterogeneous temporal data in electronic health records'. [J. Biomed. Inform. 65 (2017) 105-119]. J. Biomed. Informatics Jing Zhao, Panagiotis Papapetrou, Lars Asker, Henrik Boström
2020	J	`jnl`	Efficient conformal predictor ensembles. Neurocomputing Henrik Linusson, Ulf Johansson, Henrik Boström
2020	—	`conf`	Evaluating different approaches to calibrating conformal predictive systems. COPA Hugo Werner, Lars Carlsson, Ernst Ahlberg, Henrik Boström
2020	—	`conf`	Explaining Multivariate Time Series Forecasts: An Application to Predicting the Swedish GDP. XI-ML@KI Henrik Boström, Peter Höglund, Sven-Olof Junker, Ann-Sofie Öberg, Martin Sparr
2020	—	`conf`	Mondrian conformal regressors. COPA Henrik Boström, Ulf Johansson
2020	—	`conf`	Orthogonal Mixture of Hidden Markov Models. ECML/PKDD (1) Negar Safinianaini, Camila P. E. de Souza, Henrik Boström, Jens Lagergren
2020	J	`jnl`	Study of Hellinger Distance as a splitting metric for Random Forests in balanced and imbalanced classification datasets. Expert Syst. Appl. Ricardo Aler, José María Valls, Henrik Boström
2019	J	`jnl`	A study of data and label shift in the LIME framework. CoRR Amir Hossein Akhavan Rahnama, Henrik Boström
2019	A*	`conf`	Block-distributed Gradient Boosted Trees. SIGIR Theodore Vasiloudis, Hyunsu Cho, Henrik Boström
2019	J	`jnl`	Block-distributed Gradient Boosted Trees. CoRR Theodore Vasiloudis, Hyunsu Cho, Henrik Boström
2019	A	`conf`	Calibrating Probability Estimation Trees using Venn-Abers Predictors. SDM Ulf Johansson, Tuwe Löfström, Henrik Boström
2019	J	`jnl`	Conformal and probabilistic prediction with applications: editorial. Mach. Learn. Alexander Gammerman, Vladimir Vovk, Henrik Boström, Lars Carlsson
2019	B	`conf`	Customized Interpretable Conformal Regressors. DSAA Ulf Johansson, Cecilia Sönströd, Tuwe Löfström, Henrik Boström
2019	J	`jnl`	Efficient Venn predictors using random forests. Mach. Learn. Ulf Johansson, Tuve Löfström, Henrik Linusson, Henrik Boström
2019	B	`conf`	Gated Hidden Markov Models for Early Prediction of Outcome of Internet-Based Cognitive Behavioral Therapy. AIME Negar Safinianaini, Henrik Boström, Viktor Kaldo
2019	—	`conf`	Interpretable and specialized conformal predictors. COPA Ulf Johansson, Tuwe Löfström, Henrik Boström, Cecilia Sönströd
2019	—	`conf`	Predicting with Confidence from Survival Data. COPA Henrik Boström, Ulf Johansson, Anders Vesterberg
2019	J	`jnl`	Quantifying Uncertainty in Online Regression Forests. J. Mach. Learn. Res. Theodore Vasiloudis, Gianmarco De Francisci Morales, Henrik Boström
2018	—	`conf`	Classification with Reject Option Using Conformal Prediction. PAKDD (1) Henrik Linusson, Ulf Johansson, Henrik Boström, Tuve Löfström
2018	—	`conf`	Exploring epistaxis as an adverse effect of anti-thrombotic drugs and outdoor temperature. PETRA Jaakko Hollmén, Lars Asker, Isak Karlsson, Panagiotis Papapetrou, Henrik Boström, Birgitta Norstedt Wikner, Inger Öhman
2018	J	`jnl`	Interpretable regression trees using conformal prediction. Expert Syst. Appl. Ulf Johansson, Henrik Linusson, Tuve Löfström, Henrik Boström
2018	—	`conf`	Venn predictors for well-calibrated probability estimation trees. COPA Ulf Johansson, Tuwe Löfström, Håkan Sundell, Henrik Linusson, Anders Gidenstam, Henrik Boström
2017	J	`jnl`	Accelerating difficulty estimation for conformal regression forests. Ann. Math. Artif. Intell. Henrik Boström, Henrik Linusson, Tuve Löfström, Ulf Johansson
2017	C	`conf`	Conformal Prediction Using Random Survival Forests. ICMLA Henrik Boström, Lars Asker, Ram B. Gurung, Isak Karlsson, Tony Lindgren, Panagiotis Papapetrou
2017	J	`jnl`	Learning from heterogeneous temporal data in electronic health records. J. Biomed. Informatics Jing Zhao, Panagiotis Papapetrou, Lars Asker, Henrik Boström
2017	—	`conf`	Mining disproportional itemsets for characterizing groups of heart failure patients from administrative health records. PETRA Isak Karlsson, Panagiotis Papapetrou, Lars Asker, Henrik Boström, Hans E. Persson
2017	B	`conf`	Model-agnostic nonconformity functions for conformal classification. IJCNN Ulf Johansson, Henrik Linusson, Tuve Löfström, Henrik Boström
2017	—	`conf`	On the Calibration of Aggregated Conformal Predictors. COPA Henrik Linusson, Ulf Norinder, Henrik Boström, Ulf Johansson, Tuve Löfström
2017	—	`conf`	Using Conformal Prediction to Prioritize Compound Synthesis in Drug Discovery. COPA Ernst Ahlberg, Susanne Winiwarter, Henrik Boström, Henrik Linusson, Tuve Löfström, Ulf Norinder, Ulf Johansson, Ola Engkvist, Oscar Hammar, Claus Bendtsen, Lars Carlsson
2016	B	`ed.`	Advances in Intelligent Data Analysis XV - 15th International Symposium, IDA 2016, Stockholm, Sweden, October 13-15, 2016, Proceedings IDA Henrik Boström, Arno J. Knobbe, Carlos Soares, Panagiotis Papapetrou
2016	J	`jnl`	Clustering with Confidence: Finding Clusters with Statistical Guarantees. CoRR Andreas Henelius, Kai Puolamäki, Henrik Boström, Panagiotis Papapetrou
2016	B	`conf`	Early Random Shapelet Forest. DS Isak Karlsson, Panagiotis Papapetrou, Henrik Boström
2016	J	`jnl`	Ensembles of randomized trees using diverse distributed representations of clinical events. BMC Medical Informatics Decis. Mak. Aron Henriksson, Jing Zhao, Hercules Dalianis, Henrik Boström
2016	—	`conf`	Evaluation of a Variance-Based Nonconformity Measure for Regression Forests. COPA Henrik Boström, Henrik Linusson, Tuve Löfström, Ulf Johansson
2016	J	`jnl`	Generalized random shapelet forests. Data Min. Knowl. Discov. Isak Karlsson, Panagiotis Papapetrou, Henrik Boström
2016	B	`conf`	Identifying Factors for the Effectiveness of Treatment of Heart Failure: A Registry Study. CBMS Lars Asker, Henrik Boström, Panagiotis Papapetrou, Hans E. Persson
2016	Misc	`conf`	Learning Decision Trees from Histogram Data Using Multiple Subsets of Bins. FLAIRS Ram B. Gurung, Tony Lindgren, Henrik Boström
2016	—	`conf`	Learning from Swedish Healthcare Data. PETRA Lars Asker, Panagiotis Papapetrou, Henrik Boström
2016	—	`conf`	Predicting Adverse Drug Events Using Heterogeneous Event Sequences. ICHI Isak Karlsson, Henrik Boström
2016	—	`conf`	Reliable Confidence Predictions Using Conformal Prediction. PAKDD (1) Henrik Linusson, Ulf Johansson, Henrik Boström, Tuve Löfström
2015	J	`jnl`	Bias reduction through conditional conformal prediction. Intell. Data Anal. Tuve Löfström, Henrik Boström, Henrik Linusson, Ulf Johansson
2015	B	`conf`	Cascading adverse drug event detection in electronic health records. DSAA Jing Zhao, Aron Henriksson, Henrik Boström
2015	—	`conf`	Forests of Randomized Shapelet Trees. SLDS Isak Karlsson, Panagiotis Papapetrou, Henrik Boström
2015	—	`conf`	GoldenEye++: A Closer Look into the Black Box. SLDS Andreas Henelius, Kai Puolamäki, Isak Karlsson, Jing Zhao, Lars Asker, Henrik Boström, Panagiotis Papapetrou
2015	—	`conf`	Handling Small Calibration Sets in Mondrian Inductive Conformal Regressors. SLDS Ulf Johansson, Ernst Ahlberg, Henrik Boström, Lars Carlsson, Henrik Linusson, Cecilia Sönströd
2015	Misc	`conf`	Handling Temporality of Clinical Events for Drug Safety Surveillance. AMIA Jing Zhao, Aron Henriksson, Maria Kvist, Lars Asker, Henrik Boström
2015	—	`conf`	Modeling electronic health records in ensembles of semantic spaces for adverse drug event detection. BIBM Aron Henriksson, Jing Zhao, Henrik Boström, Hercules Dalianis
2015	B	`conf`	Modeling heterogeneous clinical sequence data in semantic space for adverse drug event detection. DSAA Aron Henriksson, Jing Zhao, Henrik Boström, Hercules Dalianis
2015	—	`conf`	Modifications to p-Values of Conformal Predictors. SLDS Lars Carlsson, Ernst Ahlberg, Henrik Boström, Ulf Johansson, Henrik Linusson
2015	J	`jnl`	Post-analysis of multi-objective optimization solutions using decision trees. Intell. Data Anal. Catarina Dudas, Amos H. C. Ng, Henrik Boström
2015	J	`jnl`	Predictive modeling of structured electronic health records for adverse drug event detection. BMC Medical Informatics Decis. Mak. Jing Zhao, Aron Henriksson, Lars Asker, Henrik Boström
2014	J	`jnl`	A peek into the black box: exploring classifiers by randomization. Data Min. Knowl. Discov. Andreas Henelius, Kai Puolamäki, Henrik Boström, Lars Asker, Panagiotis Papapetrou
2014	—	`conf`	Detecting Adverse Drug Events Using Concept Hierarchies of Clinical Codes. ICHI Jing Zhao, Aron Henriksson, Henrik Boström
2014	—	`conf`	Detecting adverse drug events with multiple representations of clinical measurements. BIBM Jing Zhao, Aron Henriksson, Lars Asker, Henrik Boström
2014	—	`conf`	Efficiency Comparison of Unstable Transductive and Inductive Conformal Classifiers. AIAI (Workshops) Henrik Linusson, Ulf Johansson, Henrik Boström, Tuve Löfström
2014	—	`conf`	Handling Sparsity with Random Forests When Predicting Adverse Drug Events from Electronic Health Records. ICHI Isak Karlsson, Henrik Boström
2014	J	`jnl`	Integration of data mining and multi-objective optimisation for decision support in production systems development. Int. J. Comput. Integr. Manuf. Catarina Dudas, Amos H. C. Ng, Leif Pehrsson, Henrik Boström
2014	—	`conf`	Mining candidates for adverse drug interactions in electronic patient records. PETRA Lars Asker, Henrik Boström, Isak Karlsson, Panagiotis Papapetrou, Jing Zhao
2014	J	`jnl`	Regression conformal prediction with random forests. Mach. Learn. Ulf Johansson, Henrik Boström, Tuve Löfström, Henrik Linusson
2014	—	`conf`	Regression trees for streaming data with local performance guarantees. IEEE BigData Ulf Johansson, Cecilia Sönströd, Henrik Linusson, Henrik Boström
2014	—	`conf`	Rule Extraction with Guaranteed Fidelity. AIAI (Workshops) Ulf Johansson, Rikard König, Henrik Linusson, Tuve Löfström, Henrik Boström
2014	—	`conf`	gpuRF and gpuERT: Efficient and Scalable GPU Algorithms for Decision Tree Ensembles. IPDPS Workshops Karl Jansson, Håkan Sundell, Henrik Boström
2013	J	`jnl`	Comparative analysis of the use of chemoinformatics-based and substructure-based descriptors for quantitative structure-activity relationship (QSAR) modeling. Intell. Data Anal. Thashmee Karunaratne, Henrik Boström, Ulf Norinder
2013	A*	`conf`	Conformal Prediction Using Decision Trees. ICDM Ulf Johansson, Henrik Boström, Tuve Löfström
2013	B	`conf`	Effective utilization of data in inductive conformal prediction using ensembles of neural networks. IJCNN Tuve Löfström, Ulf Johansson, Henrik Boström
2013	B	`conf`	Evolved decision trees as conformal predictors. IEEE Congress on Evolutionary Computation Ulf Johansson, Rikard König, Tuve Löfström, Henrik Boström
2013	—	`conf`	Generalization of Malaria Incidence Prediction Models by Correcting Sample Selection Bias. ADMA (2) Orlando P. Zacarias, Henrik Boström
2013	—	`conf`	Interleaving Innovization with Evolutionary Multi-Objective Optimization in Production System Simulation for Faster Convergence. LION Amos H. C. Ng, Catarina Dudas, Henrik Boström, Kalyanmoy Deb
2013	—	`conf`	Overproduce-and-select: The grim reality. CIEL Ulf Johansson, Tuve Löfström, Henrik Boström
2013	B	`conf`	Predicting Adverse Drug Events by Analyzing Electronic Patient Records. AIME Isak Karlsson, Jing Zhao, Lars Asker, Henrik Boström
2013	B	`conf`	Random brains. IJCNN Ulf Johansson, Tuve Löfström, Henrik Boström
2012	—	`conf`	Can Frequent Itemset Mining Be Efficiently and Effectively Used for Learning from Graph Data? ICMLA (1) Thashmee Karunaratne, Henrik Boström
2012	C	`conf`	Choice of dimensionality reduction methods for feature and classifier fusion with nearest neighbor classifiers. FUSION Sampath Deegalla, Henrik Boström, Keerthi Walgama
2012	—	`conf`	Extracting Patterns from Socioeconomic Databases to Characterize Small Farmers with High and Low Corn Yields in Mozambique: a Data Mining Approach. ICDM (Workshops) Constantino Sotomane, Jordi Gallego-Ayala, Lars Asker, Henrik Boström, Venâncio Massingue
2012	J	`jnl`	Forests of Probability Estimation Trees. Int. J. Pattern Recognit. Artif. Intell. Henrik Boström
2012	J	`jnl`	Introducing Uncertainty in Predictive Modeling - Friend or Foe? J. Chem. Inf. Model. Ulf Norinder, Henrik Boström
2012	J	`jnl`	Obtaining accurate and comprehensible classifiers using oracle coaching. Intell. Data Anal. Ulf Johansson, Cecilia Sönströd, Tuve Löfström, Henrik Boström
2011	—	`conf`	Concurrent Learning of Large-Scale Random Forests. SCAI Henrik Boström
2010	B	`conf`	Comparing methods for generating diverse ensembles of artificial neural networks. IJCNN Tuve Löfström, Ulf Johansson, Henrik Boström
2010	B	`conf`	Pin-pointing concept descriptions. SMC Cecilia Sönströd, Ulf Johansson, Henrik Boström, Ulf Norinder
2010	C	`conf`	Pre-Processing Structured Data for Standard Machine Learning Algorithms by Supervised Graph Propositionalization - A Case Study with Medicinal Chemistry Datasets. ICMLA Thashmee Karunaratne, Henrik Boström, Ulf Norinder
2009	C	`conf`	Ensemble member selection using multi-objective optimization. CIDM Tuve Löfström, Ulf Johansson, Henrik Boström
2009	C	`conf`	Fusion of dimensionality reduction methods: A case study in microarray classification. FUSION Sampath Deegalla, Henrik Boström
2009	C	`conf`	Graph Propositionalization for Random Forests. ICMLA Thashmee Karunaratne, Henrik Boström
2009	C	`conf`	Improving Fusion of Dimensionality Reduction Methods for Nearest Neighbor Classification. ICMLA Sampath Deegalla, Henrik Boström
2009	—	`conf`	Using uncertain chemical and thermal data to predict product quality in a casting process. KDD Workshop on Knowledge Discovery from Uncertain Data Catarina Dudas, Henrik Boström
2008	—	`conf`	A study on class-specifically discounted belief for ensemble classifiers. MFI Ronnie Johansson, Henrik Boström, Alexander Karlsson
2008	C	`conf`	Calibrating Random Forests. ICMLA Henrik Boström
2008	—	`conf`	Chipper - A Novel Algorithm for Concept Description. SCAI Ulf Johansson, Cecilia Sönströd, Tuve Löfström, Henrik Boström
2008	C	`conf`	Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes. ICMLA Cecilia Sönströd, Ulf Johansson, Ulf Norinder, Henrik Boström
2008	Misc	`conf`	Extending Nearest Neighbor Classification with Spheres of Confidence. FLAIRS Ulf Johansson, Henrik Boström, Rikard König
2008	C	`conf`	On evidential combination rules for ensemble classifiers. FUSION Henrik Boström, Ronnie Johansson, Alexander Karlsson
2008	C	`conf`	On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers. ICMLA Tuve Löfström, Ulf Johansson, Henrik Boström
2008	B	`conf`	The problem with ranking ensembles based on training or validation performance. IJCNN Ulf Johansson, Tuve Löfström, Henrik Boström
2007	C	`conf`	Classification of Microarrays with kNN: Comparison of Dimensionality Reduction Methods. IDEAL Sampath Deegalla, Henrik Boström
2007	C	`conf`	Estimating class probabilities in random forests. ICMLA Henrik Boström
2007	C	`conf`	Feature vs. classifier fusion for predictive data mining a case study in pesticide classification. FUSION Henrik Boström
2007	A	`conf`	Maximizing the Area under the ROC Curve with Decision Lists and Rule Sets. SDM Henrik Boström
2007	—	`conf`	Using Background Knowledge for Graph Based Learning: A Case Study in Chemoinformatics. IMECS Thashmee Karunaratne, Henrik Boström
2006	—	`conf`	Learning to classify structured data by graph propositionalization. Computational Intelligence Thashmee Karunaratne, Henrik Boström
2006	C	`conf`	Reducing High-Dimensional Data by Principal Component Analysis vs. Random Projection for Nearest Neighbor Classification. ICMLA Sampath Deegalla, Henrik Boström
2004	J	`jnl`	Resolving rule conflicts with double induction. Intell. Data Anal. Tony Lindgren, Henrik Boström
2003	B	`conf`	Resolving Rule Conflicts with Double Induction. IDA Tony Lindgren, Henrik Boström
2002	B	`conf`	Classification with Intersecting Rules. ALT Tony Lindgren, Henrik Boström
2002	—	`conf`	Rule Induction for Classification of Gene Expression Array Data. PKDD Per Lidén, Lars Asker, Henrik Boström
2001	C	`conf`	Automatic Keyword Extraction Using Domain Knowledge. CICLing Anette Hulth, Jussi Karlgren, Anna Jonsson, Henrik Boström, Lars Asker
2001	J	`jnl`	Boosting interval based literals. Intell. Data Anal. Juan J. Rodríguez Diez, Carlos Alonso González, Henrik Boström
2001	B	`conf`	Classifying Uncovered Examples by Rule Stretching. ILP Martin Eineborg, Henrik Boström
2001	—	`conf`	Learning to recognize brain specific proteins based on low-level features from on-line prediction servers. BIOKDD Mikael Huss, Henrik Boström, Lars Asker, Joakim Cöster
2000	—	`conf`	Learning First Order Logic Time Series Classifiers. ILP Work-in-progress reports Juan José Rodríguez, Carlos J. Alonso, Henrik Boström
2000	—	`conf`	Learning First Order Logic Time Series Classifiers: Rules and Boosting. PKDD Juan J. Rodríguez Diez, Carlos Alonso González, Henrik Boström
1999	B	`conf`	Combining Divide-and-Conquer and Separate-and-Conquer for Efficient and Effective Rule Induction. ILP Henrik Boström, Lars Asker
1999	J	`jnl`	Induction of Logic Programs by Example-Guided Unfolding. J. Log. Program. Henrik Boström, Peter Idestam-Almquist
1999	—	`conf`	Induction of Recursive Transfer Rules. Learning Language in Logic Henrik Boström
1998	—	`conf`	Predicate Invention and Learning from Positive Examples Only. ECML Henrik Boström
1997	J	`jnl`	IMPUT: An Interactive Learning Tool Based on Program Specialization. Intell. Data Anal. Zoltán Alexin, Tibor Gyimóthy, Henrik Boström
1996	A	`conf`	Integrating Algorithmic Debugging and Unfolding Transformation in an Interactive Learner. ECAI Zoltán Alexin, Tibor Gyimóthy, Henrik Boström
1996	A*	`conf`	Theory-Guideed Induction of Logic Programs by Inference of Regular Languages. ICML Henrik Boström
1995	A*	`conf`	Covering vs. Divide-and-Conquer for Top-Down Induction of Logic Programs. IJCAI Henrik Boström
1995	—	`conf`	JIGSAW: Puzzling together RUTH and SPECTRE (Extended Abstract). ECML Hilde Adé, Henrik Boström
1995	—	`conf`	Specialization of Recursive Predicates. ECML Henrik Boström
1993	—	`conf`	Improving Example-Guided Unfolding. ECML Henrik Boström
1991	—	`conf`	Optimizing Horn Clause Logic Programs for Particular Modes of Use: An Analysis of Explanation-Based Learning and Partial Evaluation. SCAI Carl Gustaf Jansson, Henrik Boström, Peter Idestam-Almquist
1990	—	`conf`	Generalizing the Order of Goals as an Approach to Generalizing Number. ML Henrik Boström