Support Vector Machines with Example Dependent Costs. - Ulf Brefeld; Peter Geibel; Fritz Wysotzki (ECML, 2003)

Learning Linear Classifiers Sensitive to Example Dependent and Noisy Costs. - Peter Geibel; Ulf Brefeld; Fritz Wysotzki (IDA, 2003)

Co-EM support vector learning. - Ulf Brefeld; Tobias Scheffer (ICML, 2004)

Multi-View Lernen. - Ulf Brefeld; Steffen Bickel; Tobias Scheffer (LWA, 2004)

Perceptron and SVM learning with generalized cost models. - Peter Geibel; Ulf Brefeld; Fritz Wysotzki (Intell. Data Anal., 2004)

Multi-view Discriminative Sequential Learning. - Ulf Brefeld; Christoph Büscher; Tobias Scheffer (ECML, 2005)

Multi-View Hidden Markov Perceptrons. - Ulf Brefeld; Christoph Büscher; Tobias Scheffer (LWA, 2005)

Systematic feature evaluation for gene name recognition. - Jörg Hakenberg; Steffen Bickel; Conrad Plake; Ulf Brefeld; Hagen Zahn; Lukas Faulstich; Ulf Leser; Tobias Scheffer (BMC Bioinform., 2005)

Efficient co-regularised least squares regression. - Ulf Brefeld; Thomas Gärtner 001; Tobias Scheffer; Stefan Wrobel (ICML, 2006)

Semi-supervised learning for structured output variables. - Ulf Brefeld; Tobias Scheffer (ICML, 2006)

Supervised clustering of streaming data for email batch detection. - Peter Haider; Ulf Brefeld; Tobias Scheffer (ICML, 2007)

Transductive support vector machines for structured variables. - Alexander Zien; Ulf Brefeld; Tobias Scheffer (ICML, 2007)

Support Vector Machines for Collective Inference. - Ulf Brefeld; Thoralf Klein; Tobias Scheffer (MLG, 2007)

Semi-supervised structured prediction models. - Ulf Brefeld (2007)

Automatic feature selection for anomaly detection. - Marius Kloft; Ulf Brefeld; Patrick Düssel; Christian Gehl; Pavel Laskov (AISec, 2008)

Exact and Approximate Inference for Annotating Graphs with Structural SVMs. - Thoralf Klein; Ulf Brefeld; Tobias Scheffer (ECML/PKDD (1), 2008)

Efficient Classification of Images with Taxonomies. - Alexander Binder; Motoaki Kawanabe; Ulf Brefeld (ACCV (3), 2009)

Active learning for network intrusion detection. - Nico Görnitz; Marius Kloft; Konrad Rieck; Ulf Brefeld (AISec, 2009)

Efficient and Accurate Lp-Norm Multiple Kernel Learning. - Marius Kloft; Ulf Brefeld; Sören Sonnenburg; Pavel Laskov; Klaus-Robert Müller; Alexander Zien (NIPS, 2009)

Active and Semi-supervised Data Domain Description. - Nico Görnitz; Marius Kloft; Ulf Brefeld (ECML/PKDD (1), 2009)

Feature Selection for Density Level-Sets. - Marius Kloft; Shinichi Nakajima; Ulf Brefeld (ECML/PKDD (1), 2009)

Non-Sparse Regularization and Efficient Training with Multiple Kernels - Marius Kloft; Ulf Brefeld; Sören Sonnenburg; Alexander Zien (CoRR, 2010)

Approximate Tree Kernels. - Konrad Rieck; Tammo Krueger; Ulf Brefeld; Klaus-Robert Müller (J. Mach. Learn. Res., 2010)

Eighth workshop on mining and learning with graphs. - Ulf Brefeld; Lise Getoor; Sofus A. Macskassy (SIGKDD Explor., 2010)

Hybrid models for future event prediction. - Giuseppe Amodeo; Roi Blanco; Ulf Brefeld (CIKM, 2011)

Learning to rank user intent. - Giorgos Giannopoulos; Ulf Brefeld; Theodore Dalamagas 001; Timos K. Sellis (CIKM, 2011)

Learning from Partially Annotated Sequences. - Eraldo R. Fernandes; Ulf Brefeld (ECML/PKDD (1), 2011)

Document assignment in multi-site search engines. - Ulf Brefeld; Berkant Barla Cambazoglu; Flavio Paiva Junqueira (WSDM, 2011)

Insights from Classifying Visual Concepts with Multiple Kernel Learning - Alexander Binder; Shinichi Nakajima; Marius Kloft; Christina Müller; Wojciech Samek; Ulf Brefeld; Klaus-Robert Müller; Motoaki Kawanabe (CoRR, 2011)

StructRank: A New Approach for Ligand-Based Virtual Screening. - Fabian Rathke; Katja Hansen; Ulf Brefeld; Klaus-Robert Müller (J. Chem. Inf. Model., 2011)

lp-Norm Multiple Kernel Learning. - Marius Kloft; Ulf Brefeld; Sören Sonnenburg; Alexander Zien (J. Mach. Learn. Res., 2011)

Discriminative clustering for market segmentation. - Peter Haider; Luca Chiarandini; Ulf Brefeld (KDD, 2012)

Adaptive Speeded Tests. - Daniel Bengs; Ulf Brefeld (LWA, 2013)

Learning Shortest Paths for Word Graphs. - Emmanouil Tzouridis; Ulf Brefeld (LWA, 2013)

Finding Similar Movements in Positional Data Streams. - Jens Haase; Ulf Brefeld (MLSA@PKDD/ECML, 2013)

Toward Supervised Anomaly Detection. - Nico Görnitz; Marius Kloft; Konrad Rieck; Ulf Brefeld (J. Artif. Intell. Res., 2013)

An Off-the-shelf Approach to Authorship Attribution. - Jamal Abdul Nasir; Nico Görnitz; Ulf Brefeld (COLING, 2014)

Learning to Summarise Related Sentences. - Emmanouil Tzouridis; Jamal Abdul Nasir; Ulf Brefeld (COLING, 2014)

Computer-based Adaptive Speed Tests. - Daniel Bengs; Ulf Brefeld (EDM, 2014)

Interdisciplinary Machine Learning. - Ulf Brefeld (LWA, 2014)

Using Wikipedia for Cross-Language Named Entity Recognition. - Eraldo R. Fernandes; Ulf Brefeld; Roi Blanco; Jordi Atserias (MSM/MUSE/SenseML, 2014)

Mining Positional Data Streams. - Jens Haase; Ulf Brefeld (NFMCP, 2014)

Factored MDPs for detecting topics of user sessions. - Maryam Tavakol; Ulf Brefeld (RecSys, 2014)

Generalising IRT to Discriminate Between Examinees. - Ahcène Boubekki; Ulf Brefeld; Thomas Delacroix (EDM, 2015)

Toward Data-Driven Analyses of Electronic Text Books. - Ahcène Boubekki; Ulf Kröhne; Frank Goldhammer; Waltraud Schreiber; Ulf Brefeld (EDM, 2015)

Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer. - Markus Brandt; Ulf Brefeld (MLSA@PKDD/ECML, 2015)

Multi-view learning with dependent views. - Ulf Brefeld (SAC, 2015)

Data-Driven Analyses of Electronic Text Books. - Ahcène Boubekki; Ulf Kröhne; Frank Goldhammer; Waltraud Schreiber; Ulf Brefeld (Solving Large Scale Learning Tasks, 2016)

Feature Extraction and Aggregation for Predicting the EURO 2016. - Maryam Tavakol; Hamid Zafartavanaelmi; Ulf Brefeld (MLSA@PKDD/ECML, 2016)

Spatio-temporal convolution kernels. - Konstantin Knauf; Daniel Memmert; Ulf Brefeld (Mach. Learn., 2016)

Predicting the future performance of soccer players. - Cornelius Arndt; Ulf Brefeld (Stat. Anal. Data Min., 2016)

Frame-based Data Factorizations. - Sebastian Mair 001; Ahcène Boubekki; Ulf Brefeld (ICML, 2017)

Propagating Maximum Capacities for Recommendation. - Ahcène Boubekki; Ulf Brefeld; Cláudio Leonardo Lucchesi; Wolfgang Stille (KI, 2017)

Infinite Mixtures of Markov Chains. - Jan Reubold; Ahcène Boubekki; Thorsten Strufe; Ulf Brefeld (NFMCP@PKDD/ECML, 2017)

A Unified Contextual Bandit Framework for Long- and Short-Term Recommendations. - Maryam Tavakol; Ulf Brefeld (ECML/PKDD (2), 2017)

Guest editorial: Special issue on sports analytics. - Ulf Brefeld; Albrecht Zimmermann (Data Min. Knowl. Discov., 2017)

Mining User Trajectories in Electronic Text Books. - Ahcène Boubekki; Shailee Jain; Ulf Brefeld (EDM, 2018)

MDP-based Itinerary Recommendation using Geo-Tagged Social Media. - Radhika Gaonkar; Maryam Tavakol; Ulf Brefeld (IDA, 2018)

Frame-Based Optimal Design. - Sebastian Mair 001; Yannick Rudolph; Vanessa Closius; Ulf Brefeld (ECML/PKDD (2), 2018)

Distributed robust Gaussian Process regression. - Sebastian Mair 001; Ulf Brefeld (Knowl. Inf. Syst., 2018)

Personalized Transaction Kernels for Recommendation Using MCTS. - Maryam Tavakol; Tobias Joppen; Ulf Brefeld; Johannes Fürnkranz (KI, 2019)

Coresets for Archetypal Analysis. - Sebastian Mair 001; Ulf Brefeld (NeurIPS, 2019)

Predicting the Difficulty of Exercise Items for Dynamic Difficulty Adaptation in Adaptive Language Tutoring. - Irina Pandarova; Torben Schmidt; Johannes Hartig; Ahcène Boubekki; Roger Dale Jones; Ulf Brefeld (Int. J. Artif. Intell. Educ., 2019)

Learning to Rate Player Positioning in Soccer. - Uwe Dick; Ulf Brefeld (Big Data, 2019)

Probabilistic movement models and zones of control. - Ulf Brefeld; Jan Lasek; Sebastian Mair 001 (Mach. Learn., 2019)

Assessing User Behavior by Mouse Movements. - Jennifer Jorina Matthiesen; Ulf Brefeld (HCI (38), 2020)

Graph Conditional Variational Models: Too Complex for Multiagent Trajectories? - Yannick Rudolph; Ulf Brefeld; Uwe Dick (ICBINB@NeurIPS, 2020)

Principled Interpolation in Normalizing Flows. - Samuel G. Fadel; Sebastian Mair 001; Ricardo da Silva Torres; Ulf Brefeld (ECML/PKDD (2), 2021)

Machine Learning in Sports (Dagstuhl Seminar 21411). - Ulf Brefeld; Jesse Davis; Martin Lames; James J. Little (Dagstuhl Reports, 2021)

Joint optimization of an autoencoder for clustering and embedding. - Ahcène Boubekki; Michael Kampffmeyer; Ulf Brefeld; Robert Jenssen (Mach. Learn., 2021)

Modeling Conditional Dependencies in Multiagent Trajectories. - Yannick Rudolph; Ulf Brefeld (AISTATS, 2022)

Semi-Supervised Generative Models for Multiagent Trajectories. - Dennis Fassmeyer; Pascal Fassmeyer; Ulf Brefeld (NeurIPS, 2022)

Who can receive the pass? A computational model for quantifying availability in soccer. - Uwe Dick; Daniel Link 002; Ulf Brefeld (Data Min. Knowl. Discov., 2022)

Hands in Focus: Sign Language Recognition Via Top-Down Attention. - Noha A. Sarhan; Christian Wilms; Vanessa Closius; Ulf Brefeld; Simone Frintrop (ICIP, 2023)

User Authentication via Multifaceted Mouse Movements and Outlier Exposure. - Jennifer Jorina Matthiesen; Hanne Hastedt; Ulf Brefeld (IDA, 2023)

Data practices in apps from Brazil: What do privacy policies inform us about? - Valéria Quadros dos Reis; Maria E. R. Rabello; Anderson C. Lima; Guilherme P. S. Jardim; Eraldo R. Fernandes; Ulf Brefeld (J. Interact. Syst., 2023)

Computational Approaches to Strategy and Tactics in Sports (Dagstuhl Seminar 24081). - Ulf Brefeld; Jesse Davis; Laura de Jong; Stephanie Kovalchik (Dagstuhl Reports, 2024)

Toward Learning Distributions of Distributions. - Moritz Wohlstein; Ulf Brefeld (NLDL, 2025)

Interactive sequential generative models for team sports. - Dennis Fassmeyer; Moritz Cordes; Ulf Brefeld (Mach. Learn., 2025)

Masked autoencoder for multiagent trajectories. - Yannick Rudolph; Ulf Brefeld (Mach. Learn., 2025)

Common Data Format (CDF): A Standardized Format for Match-Data in Football (Soccer). - Gabriel Anzer; Kilian Arnsmeyer; Pascal Bauer; Joris Bekkers; Ulf Brefeld; Jesse Davis; Nicolas Evans; Matthias Kempe; Samuel J. Robertson; Joshua Wyatt Smith; Jan Van Haaren (CoRR, 2025)