Email: kristian.kersting At sign

cs.tu-dortmund.de
Phone:
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About

As of May 1st, 2017, I moved to the TU Darmstadt University. For now I am still teaching a class at the TU Dortmund University.

Kristian Kersting is an Associate Professor in the Computer Science Department at the Technical University of Dortmund, Germany. He received his Ph.D. from the University of Freiburg, Germany, in 2006 and moved to the Fraunhofer IAIS and the University of Bonn using a Fraunhofer ATTRACT Fellowship in 2008 after a PostDoc at MIT, USA. Before moving to the TU Dortmund University in 2013, he was appointed Assistant Professor for Spatio-Temporal Patterns in Agriculture at the University of Bonn in 2012. Additionally, he was Adjunct Assistant Professor at the Medical School of the Wake Forest University, USA, in 2012. Interactive CV

His main research interests are data mining, machine learning, and statistical relational artificial intelligence, with applications to medicine, plant phenotpying, traffic, and collective attention. He has published over 150 peer-reviewed technical papers and received

the ECCAI Dissertation Award 2006 for the best AI dissertation in Europe,
the Best Student Paper Award of the European Conference on Machine Learning (ECML) in 2006,
the Best Poster Award of the ACM SIGSPATIAL Advances in Geographic Information Systems (GIS) in 2011,
an Outstanding PC Member Award of the AAAI Conference on Artificial Intelligence (AAAI) in 2013,
the Best Paper Presentation Award of the New Challenges in Neural Computations (NC^2) workshop in 2015,
the Best Paper Award of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE) in 2015, and
an Outstanding Reviewer Award of the European Conference on Computer Vision (ECCV) in 2016, and
a Distinguished Lecturer Award of the Faculty of Mathematics and Computer Science at the Friedrich-Schiller-University Jena (Winter Term 2016/2017).

He was also a ERCIM Cor Baayen Award 2009 finalist, gave several tutorials at top conferences, and co-chaired SymInfOpt, BeyondLabeler, BUDA, CMPL, CoLISD, MLG, and SRL as well as the AAAI Student Abstract track and the Starting AI Research Symposium (STAIRS). Together with Stuart Russell (Berkeley), Leslie Kaelbling (MIT), Alon Halevy (Goolge), Sriraam Natarajan (Indiana) and Lilyana Mihalkova (Google) he cofounded the international workshop series on Statistical Relational AI. He served as area chair/senior PC for several top conference and co-chaired ECML PKDD 2013, the premier European venue for Machine Learning and Data Mining, the Best Paper Award Committee of KDD 2015, the premier international venue for Data Mining, and UAI 2017, one of the premier international conferences on research related to knowledge representation, learning, and reasoning in the presence of uncertainty. Currently, he is an action editor of JAIR, AIJ, DAMI, and MLJ as well as on the editorial boards of the NGC, Information, and Big Data and Cognitive Computing.

Software and other things can be found in our Web Lab.

Publications as listed below can also be found at loop, DBLP, SemanticScholar, and GOOGLE Scholar Citations.

	Luc De Raedt, Kristian Kersting, Sriraam Natarajan, David Poole, Statistical Relational Artificial Intelligence: Logic, Probability, and Computation. Morgan and Claypool Publishers,Synthesis Lectures on Artificial Intelligence and Machine Learning, ISBN: 9781627058414, 2016. See also our IJCAI 2016 tutorial
	Jörg Lässig, Kristian Kersting, Katharina Morik, Computational Sustainability. Studies in Computational Intelligence, Volume 645 2016, Springer, ISBN: 978-3-319-31856-1, 2016.
	Sriraam Natarajan, Tushar Khot, Kristian Kersting and Jude Shavlik, Boosted Statistical Relational Learners: From Benchmarks to Data-Driven Medicine. SpringerBriefs in Computer Science, ISBN: 978-3-319-13643-1, 2015.
	Luc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton, Probabilistic Inductive Logic Programming: Theory and Applications. LNCS Vol. 4911, Springer, ISBN: 78-3-540-78651-1, 2008.
	Kristian Kersting, An Inductive Logic Programming Approach to Statistical Relational Learning. IOS Press, ISBN: 978-1-58603-674-4, 2006.
	Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2013), Prague, Czech Republic, September 23-27, 2013, Proceedings, Parts I-III. Lecture Notes in Computer Science 8188-8190, Springer 2013, ISBN 978-3-642-40987-5
	Kristian Kersting, Marc Toussaint: Proceedings of the Sixth Starting AI Researchers' Symposium (STAIRS 2012), Montpellier, France, 27-28 August 2012. Frontiers in Artificial Intelligence and Applications 241, IOS Press 2012, ISBN 978-1-61499-095-6

Current Group Members:

Elena Erdmann, Martin Mladenov, Alejandro Molina

Alumni:

Babak Ahmadi (BitStar), Timothy Ellersiek (goedle.io), Fabian Hadiji (goedle.io), Ahmed Jawad (Allianz), Marc Müller (goedle.io), Marion Neumann (Washington University in St. Louis.), Mirwaes Wahabzada (Uni Bonn), Zhao Xu (NEC)

Media Coverage:

Interview@MLconf 2016 see also the YouTube video, "Big-Data gegen Pflanzenkrankheiten" Editor's Pick in Plant 2030 News, "Der digitale Pflanzen-Doktor: Eine neuartige Software erkennt Pflanzenkrankheiten bereits im Frühstadium"@Pflanzenforschung.de 03/16 , "Data Mining"@Talk-Magazine "THINK BIG: Große Daten, große Fragen", "Algorithmen — Wer kontrolliert die neuen Machthaber?"@nr15 - netzwerk Recherche Jahrestagung 2015, "Big Data aus der Wurzel"@Bild der Wissenschaften Plus, "Humans as Sensors"@eldoradio.de, "Die Diskussion nach Snowden weitertragen"@nrch.de/blog14, "Neuer Studiengang Datenjournalismus"@do1.TV, "Datenschätze: Neuer Rohstoff für Journalisten"@digitale-zukunft-koeln.de, "Detektivarbeit im Datenberg"@Mundo 20/2014, "Yes, Facebook's popularity will decline"@ZDNet.com, "Auf Social Media Intelligence kommt es an"@absatzwirtschaft.de,"How did Vintage Memes Go Viral?"@The Connectivist, "Mine Your Language"@New Scientist,"Germany Inspires Innovation"@Scientific American, "Game Miners grapple with Massive Data"@Science, "Phantasialand forscht"@Kölner Express, "Akademiker gehen ins Ausland - und kommen wieder zurück"@Frankfurter Allgemeine Zeitung 11 September 2010, "Beziehungen auf der Spur"@WeiterVorn 1.10

Selected Invited Talks:

"Thinking Machine Learning": NIPS 2016 Workshop on Neurorobotics: A Chance for New Ideas, Algorithms and Approaches; "Declarative Data Science Programming": 25th Annual Machine Learning Conference of Belgium and The Netherlands (BeneLearn 2016); "Collective Attention on the Web": 19th International Conference on Discovery Science (DS 2016); "Declarative Programming for Statistical ML": The 2016 Machine Learning Conference (MLconf Seattle); "Daten! Sind sie Leben?" Kneipengespräch der "Lust an Wissenschaft?" 2016 Serie der Mercator Global Young Faculty; "Declarative Data Science Programming": Software Engineering and Machine Learning Workshop at the 10th Heinz Nixdorf Symposium 2016;"Lifted Machine Learning": International School on Human-Centred Computing (HCC 2016); "Collective Attention on the Web": International School and Conference on Network Science (NetSci-X 2016); "Democratization of Optimization" AAAI 2016 Workshop on Declarative Learning Based Programming (DeLBP 2016);"Democratization of Optimization": 14th Conference of the Italian Association for Artificial Intelligence (AI*IA 2015), "Democratization of Optimization": 5th International Workshop on Statistical Relational AI (StarAI 2015), "Democratization of Optimization": IJCAI 2015 Invited Sister Conference Presentations ML Track, "Poisson Dependency Networks": 2nd International Workshop on Mining Urban Data (MUD 2015), "Lifted Probabilistic Inference": Frontiers in AI@ECAI 2012, "From Lifted Probabilistic Inference to Lifted Linear Programming": 7th International Workshop on Uncertainty Reasoning for the Semantic Web (URSW 2011), "Increasing Representational Power and Scaling Inference in Reinforcement Learning": 9th European Workshop on Reinforcement Learning (EWRL 2011), "Perception and Prediction Beyond the Here and Now": 2nd International Workshop on Mining Ubiquitous and Social Environments (MUSE 2011), "Lifted Message Passing": International Workshop on Graphical Models in Robotics (GraphBot 2010), "Relations and Probabilities: Friends, not Foes": Lernen, Wissen, Adaptivität (LWA 2009), "Probabilistic Logic Learning and Reasoning": 14th Annual Machine Learning Conference of Belgium and the Netherlands (BeneLearn 2005),

Selected (Program Committee) Co-Chairs:

UAI'17, ECML PKDD'13

ICML'18 Workshop Chair, KDD'15 Best Paper Award Committee

AAAI'14 Student Abstract and Poster Program, AAAI'13 Student Abstract and Poster Program, STAIRS'12, AAAI'12 Student Abstract and Poster Program

SymInfOpt@AAAI'17, BeyondLabeler@IJCAI'16, StarAI@AAAI'14, Buda@PODS'14, SRL@ICML'12, StarAI@UAI'12, CoLISD@ECMLPKDD'12, CMPL@NIPS'11, MLG@KDD'11, StarAI@AAAI'10, SRL'09, MLG'07, Dagstuhl Seminar 07161

Selected Program Committees/Reviewer:

SIGMOD'17, IJCAI'17 (SPC), AAAI'17 (SPC), ACML'16 (SPC), ICDM'16, UAI'16, ECCV'16, ECML PKDD'16 (AC), ECAI'16, IJCAI'16, ICML'16, KDD'16 (AC), AAAI'16 (SPC), DS'16, KI'16, MOD'16, ICDM'15, NIPS'15, ECML PKDD'15 (GEB, AC), IJCAI'15 (SPC), MPD'15, SUM'15, CVPR'15, ICML'15, CoDS'15, AAAI'15 (Main, AIW), AAAI'14 (SPC, SM, SA) , ECML PKDD'14 (GEB, AC), ICDM'14 (AC), ECAI'14 (AC), PODS'14, KDD'14 (PC and Best Paper Award Committee), UAI'14, NIPS'14, SDM'14, ACML'14 (AC and Best Paper Award Committee), CIKM'14 (KM Track), ESWC'14, ILP'14, KR'14, PGM'14, DS'14, CoDS'14, DATA'14, LTPM'14, Know@LOD'14, MUSE'14, SenseML'14, ICML'10 (AC and Best Paper Award Committee)

(Associate) Editor:

Journal of Artificial Intelligence Research (AE), Machine Learning Journal (AE), Data Mining and Knowledge Discovery (AE), Artificial Intelligence Journal (AE), New Computing Generation, Information, and Big Data and Cognitive Computing.

Tutorials:

"Statistical Relational Artificial Intelligence: Logic, Probability, and Computation", AAAI 2017; "Data-Diven Plant Phenotyping" PHENOMICS Workshop Berlin 2016; "Statistical Relational Artificial Intelligence: Logic, Probability, and Computation" IJCAI 2016; "Statistical Relational Artificial Intelligence: Logic, Probability, and Computation", HCC 2016; "60 Years of Artificial Intelligence - Where are we?" Summer Academy of the German National Academic Foundation 2015; "Statistical (Relational) Learning and Lifted inference" MLSMA 2014; "Lifted Approximate Inference: Methods and Theory" AAAI 2014; "Combining Logic and Probability: Languages, Algorithms, and Applications" AAAI 2013; "Factorizing Gigantic Matrices" ECMLPKDD 2011; "Combining Logic and Probability: Languages, Algorithms, and Applications" UAI 2011; "Lifted Inference in Probabilistic Logical Models" IJCAI 2011; "Statistical Relational Learning" MLSS 2010; "First-order Planning" ICAPS 2008; "SRL without Tears: An ILP Perspective on SRL" ILP 2008; "Decision-Theoretic Planning and Learning in Relational Domains" AAAI 2008; "Probabilistic Inductive Logic Learning" ECMLPKDD 2005,; "Probabilistic Inductive Logic Learning" IDA 2005; "Probabilistic Logic Learning" ICML 2004

Scientific Advisor:

	pflegix.de, seit 2016.
	heydeal.de, since 2016.
	goedle.io, since 2015.
	ABIDA - ASSESING BIG DATA, since 2015.
	GameAnalytics, 2012-2014.

bla

Projects

Research Topics

Publications

Molina/etal/2018a	Molina, Alejandro and Munteanu, Alexander and Kersting, Kristian. Core Dependency Networks. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2018.
Alfeld/etal/2017a	Alfeld, Matthias and Wahabzada, Mirwaes and Bauckhage, Christian and Kersting, Kristian and van der Snickt, Geert and Noble, Petria Janssens, Koen and Wellenreuther, Gerd and Falkenberg, Gerald. Simplex Volume Maximization (SiVM): A matrix factorization algorithm with non-negative constrains and low computing demands for the interpretation of full spectral X-ray fluorescence imaging data. In Microchemical Journal, Vol. 132, pages 179-184, 2017.
Dehbi/etal/2017a	Dehbi, Youness and Hadiji, Fabian and Gröger, Gerhard and Kersting, Kristian and Plümer, Lutz. Statistical Relational Learning of Grammar Rules for 3D Building Reconstruction. In Transactions in GIS, Vol. 21, No. 1, pages 134-150, 2017.
Kersting/etal/2017	Kersting, Kristian and Mladenov, Martin and Tokmakov, Pavel. Relational Linear Programming. In Artificial Intelligence Journal (AIJ), Vol. 244, pages 188-216, 2017.
Kriege/etal/2017a	Kriege, Nils and Neumann, Marion and Morris, Christopher and Kersting, Kristian and Mutzel, Petra. A Unifying View of Explicit and Implicit Feature Maps for Structured Data: Systematic Studies of Graph Kernels. In CoRR, Vol. abs/1703.00676, 2017.
Mladenov/etal/2017b	Mladenov, Martin and Belle, Vaishak and Kersting, Kristian. The Symbolic Interior Point Method. In Satinder Singh and Shaul Markovitch (editors), Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), AAAI Press, 2017.
Molina/etal/2017a	Molina, Alejandro and Natarajan, Sriraam and Kersting, Kristian. Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), pages 2357--2363, 2017.
Alfed/etal/2016a	Alfeld, Matthias and Wahabzada, Mirwaes and Bauckhage, Christian and Kersting, Kristian and Wellenreuther, Gerd and Barriobero-Vila, Pere and Requena, Guillermo and Boesenberg, Ulrike and Falkenberg, Gerald. Non-negative matrix factorization for the near real-time interpretation of absorption effects in elemental distribution images acquired by X-ray fluorescence imaging. In Journal of Synchrotron Radiation, Vol. 23, No. Pt 2, pages 579-589, 2016.
Bauckhage/Kersting/2016a	Bauckhage, Christian and Kersting, Kristian. Collective Attention on the Web. In Foundations and Trends in Web Science, Vol. 5, No. 1-2, pages 1-136, 2016.
Das/etal/2016a	Das, Mayukh and Wu, Yunqing and Khot, Tushar and Kersting, Kristian and Natarajan, Sriraam. Scaling Lifted Probabilistic Inference and Learning Via Graph Databases,. In Proceedings of the SIAM International Conference on Data Mining (SDM), 2016.
Erdmann/etal/2016b	Erdmann, Elena and Boczek, Karin and Koppers, Lars and von Nordheim, Gerret and Poelitz, Christian and Molina, Alejandro and Morik, Katharina and Mueller, Henrik and Rahnenfuehrer, Joerg and Kersting, Kristian. Machine Learning meets Data-Driven Journalism: Boosting International Understanding and Transparency in News Coverage. In Proceedings of the 2016 ICML Workshop on #Data4Good: Machine Learning in Social Good Applications, 2016.
Habel/etal/2015a	Habel, Lars and Molina, Alejandro and Zaksek, Thomas and Kersting, Kristian and Schreckenberg, Michael. Traffic simulations with empirical data -- How to replace missing traffic flows?. In Knoop, Victor L. and Daamen, Winnie (editors), Traffic and Granular Flow '15, pages 491-498, Springer, 2016.
Leucker/etal/2016a	Leucker, Marlene and Wahabzada, Mirwaes and Kersting, Kristian and Peter, Madlaina and Beyer, Werner and Steiner, Ulrike and Mahlein, Anne-Katrin and Oerke, Erich-Christian. Hyperspectral imaging reveals the effect of sugar beet QTLs on Cercospora leaf spot resistance. In Functional Plant Biology, Vol. 44, pages 1-9, 2016.
Mladenov/etal/2016a	Mladenov, Martin and Heinrich, Danny and Kleinhans, Leonard and Gonsior, Felix and Kersting, Kristian. RELOOP: A Python-Embedded Declarative Language for Relational Optimization. In Working Notes of the First AAAI Workshop on Declarative Learning Based Programming (DeLBP), AAAI Press, 2016.
Morris/etal/2016a	Morris, Christopher and Kriege, Nils and Kersting, Kristian and Mutzel, Petra. Faster Kernels for Graphs with Continuous Attributes via Hashing. In IEEE International Conference on Data Mining (ICDM), pages 1095--1100, 2016.
Odom/etal/2016a	Odom, P and Kumaraswamy, R. and Kersting, K. and Natarajan, S.. Learning through Advice-Seeking via Transfer. In James Cussens and Alessandra Russo (editors), Proceedings of the 26th International Conference on Inductive Logic (ILP), Springer, 2016.
Szymanski/etal/2016a	Szymanski, Piotr and Kajdanowicz, Tomasz and Kersting, Kristian. How Is a Data-Driven Approach Better than Random Choice in Label Space Division for Multi-Label Classification?. In Entropy, Vol. 18, No. 8, pages 282, 2016.
Taylor/etal/2016a	Taylor, Joseph and Sharmanska, and Kersting, Kristian and Weir, David and Quadrianto, Novi. Learning using Unselected Features (LUFe). In S. Kambhampati (editors), Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), 2016.
Wahabzada/etal/2016a	Wahabzada, Mirwaes and Mahlein, Anne-Katrin and Bauckhage, Christian and Steiner, Ulrike and Oerke, Erich-Christian and Kersting, Kristian. Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of Plants. In Scientific Reports (Nature), Vol. 6, 22482, 2016.
Yang/etal/2016a	Yang, Shuo and Khot, Tushar and Kersting, Kristian and Natarajan, Sriraam. Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), AAAI Press, 2016.
Bauckhage/etal/2015a	Bauckhage, Christian and Kersting, Kristian and Hadiji, Fabian. Parameterizing the Distance Distribution of Undirected Networks. In Tom Heskes and Marina Meila (editors), Proceedings of the 31th Conference on Uncertainty in Artificial Intelligence (UAI), AUAI, 2015.
Bauckhage/etal/2015b	Bauckhage, Christian and Kersting, Kristian and Hadiji, Fabian. How Viral are Viral Movies?. In Proceedings of the 9th International AAAI Conference on Web and Social Media (ICWSM), 2015.
Bauckhage/etal/2015c	Bauckhage, Christian and Kersting, Kristian and Hoppe, Florian and Thurau, Christian. Archetypal Analysis as an Autoencoder. In Barbara Hammer, Thomas Martinetz, and Thomas Villmann (editors), Working Notes of the GCPR 2015 Workshop on New Challenges in Neural Computation, 2015.
Hadiji/etal/2015a	Hadiji, Fabian and Mladenov, Martin and Bauckhage, Christian and Kersting, Kristian. Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI), 2015.
Hadiji/etal/2015b	Hadiji, Fabian and Molina, Alejandro and Natarajan, Sriraam and Kersting, Kristian. Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data. In Machine Learning Journal (MLJ), Vol. 100, No. 2, pages 477-507, 2015.
Ide/etal/2015a	Ide, Christoph and Hadiji, Fabian and Habel, Lars and Molina, Alejandro and Zaksek, Thomas and Schreckenberg, Michael and Kersting, Kristian. and Wietfeld, Christian. LTE Connectivity and Vehicular Traffic Prediction based on Machine Learning Approaches. In IEEE 82nd Vehicular Technology Conference (VTC-Fall), Boston, USA, 2015.
Kersting/Natarajan/2015a	Kersting, Kristian and Natarajan, Sriraam. Statistical Relational Artificial Intelligence: From Distributions through Actions to Optimization. In Künstliche Intelligenz, 2015.
Khot/etal/2015a	Khot, Tushar and Natarajan, Sriraam and Kersting, Kristian and Gutmann, Bernd and Shavlik, Jude. Gradient-based Boosting for Statistical Relational Learning: The Markov Logic Network and Missing Data Cases. In Machine Learning Journal (MLJ), 2015.
Kumaraswamy/etal/2015a	Kumaraswamy, Raksha and Odom, Phillip and Kersting, Kristian and Leake, David and Natarajan, Sriraam. Transfer Learning via Relational Type Matching. In Proceedings of the 15th IEEE International Conference on Data Mining (ICDM), IEEE, 2015.
Kuska/etal/2015a	Kuska, Matheus and Wahabzada, Mirwaes and Leuckner, Marlene and Dehne, Heinz-Wilhelm and Kersting, Kristian and Oerke, Erich-Christian and Steiner, Ulrike and Mahlein, Anne-Katrin. Hyperspectral Phenotyping on the Microscopic Scale: Towards Automated Characterization of Plant-Pathogen Interactions. In Plant Methods, 2015.
Mladenov/Kersting/2015a	Mladenov, Martin and Kersting, Kristian. Equitable Partitions of Concave Free Energies. In Tom Heskes and Marina Meila (editors), Proceedings of the 31th Conference on Uncertainty in Artificial Intelligence (UAI), AUAI, 2015.
Neumann/etal/2015a	Neumann, Marion and Huang, Shan and Marthaler, Daniel E. and Kersting, Kristian. pyGPs - A Python Library for Gaussian Process Regression and Classification. In Journal of Machine Learning Research (JMLR), 2015.
Neumann/etal/2015b	Neumann, Marion and Hallau, Lisa and Klatt, Benjamin and Kersting, Kristian and Bauckhage, Christian. Cell Phone Image-Based Plant Disease Classification. In Jun Zhaou, Xiao Bai, and Terry Caelli (editors), Computer Vision and Pattern Recognition in Environmental Informatics, IGI Global, 2015.
Neumann/etal/2015c	Neumann, Marion and Garnett, Roman and Bauckhage, Christian and Kersting, Kristian. Propagation Kernels: Efficient Graph Kernels from Propagated Information. In Machine Learning Journal (MLJ), 2015.
Sifa/etal/2015a	Sifa, Rafet and Hadiji, Fabian and Rune, Julian and Drachen, Anders and Kersting, Kristian and Bauckhage, Christian. Predicting Purchase Decisions in Free To Play Mobile Games. In 11th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), AAAI Press, 2015.
Wahabzada/etal/2015a	Wahabzada, Mirwaes and Mahlein, Anne-Katrin and Bauckhage, Christian and Steiner, Ulrike and Oerke, Erich-Christian and Kersting, Kristian. Metro Maps of Plant Disease Dynamics - Automated Mining of Differences Using Hyperspectral Images. In PLoS ONE, 2015.
Wahabzada/etal/2015b	Wahabzada, Mirwaes and Paulus, Stefan and Kersting, Kristian and Mahlein, Anne-Katrin. Automated Interpretation of 3D Laserscanned Point Clouds for Plant Organ Segmentation. In BMC Bioinformatics, 2015.
Yang/etal/2015a	Yang, Shuo and Kersting, Kristian and Terry, Greg and Carr, Jeffrey and Natarajan, Sriraam. Modeling Coronary Artery Calcification Levels From Behavioral Data in a Clinical Study. In Proceedings of the 15th Conference on Artificial Intelligence in Medicine (AIME), 2015.
Alfeld/etal/2014a	Alfeld, Matthias and Wahabzada, Mirwaes and Bauckhage, Christian and Kersting, Kristian and Falkenberg, Gerald. Non-negative factor analysis supporting the interpretation of elemental distribution images acquired by XRF. In Proceedings of 22nd International Congress on X-Ray Optics and Microanalysis (ICXOM) in Journal of Physics: Conference Series, 2014.
Apsel/etal/2104a	Apsel, Udi and Kersting, Kristian and Mladenov, Martin. Lifting Relational MAP-LPs using Cluster Signatures. In Brodley, Carla and Stone, Peter (editors), Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14), AAAI Press, 2014.
Bauckhage/atal/2014a	Bauckhage, Christian and Kersting, Kristian and Thurau, Christian. Künstliche Intelligenz für Computerspiele - Historische Entwicklung und aktuelle Trends. In Informatik Spektrum, Vol. 37, No. 6, 2014.
Bauckhage/etal/2014a	Bauckhage, Christian and Kersting, Kristian and Rastegarpanah, Bashir. Collective Attention to Social Media Evolves According to Diffusion Models. In Proceedings of the World Wide Web Conference (WWW), 2014.
Grohe/etal/2014a	Grohe, Martin and Kersting, Kristian and Mladenov, Martin and Selman, Aziz Erkal. Dimension Reduction via Colour Refinement. In Proceedings of the 22nd European Symposium on Algorithms (ESA), 2014.
Hadiji/etal/2014a	Hadiji, Fabian and Sifa, Rafet and Drachen, Anders and Thurau, Christian and Kersting, Kristian and Bauckhage, Christian. Predicting Player Churn in Free-to-play Games. In Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG), IEEE, 2014.
Hernandez/etal/2014a	Hernandez-Lobato, Daniel and Sharmanska, Viktoriia and Kersting, Kristian and Lampert, Christoph H. and Quadrianto, Novi. Mind the Nuisance: Gaussian Process Classification using Privileged Noise. In Neural Information Processing Systems (NIPS), Montreal, Quebec, Canada, 2014.
Kazemi/etal/2014a	Kazemi, Seyed Mehran and Buchman, David, and Kersting, Kristian and Natarajan, Sriraam and Poole, David. Relational Logistic Regression. In Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning (KR), 2014.
Kersting/etal/2014a	Kersting, Kristian and Mladenov, Martin and Garnett, Roman and Grohe, Martin. Power Iterated Color Refinement. In Brodley, Carla and Stone, Peter (editors), Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14), AAAI Press, 2014.
Kriege/etal/2014a	Kriege, Nils and Neumann, Marion and Kersting, Kristian and Mutzel, Petra. Explicit versus Implicit Graph Feature Maps: A Computational Phase Transition for Walk Kernels. In Kumar, Ravi and Toivonen, Hannu (editors), Proceedings of the IEEE International Conference on Data Mining (ICDM), pages 881--886, IEEE, 2014.
Mladenov/etal/2014a	Mladenov, Martin and Kersting, Kristian and Globerson, Armir. Efficient Lifting of MAP LP Relaxations Using k-Locality. In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS) in Journal of Machine Learning Research ( JMLR) Workshop & Conference Proceedings Series, Vol. 33, 2014.
Mladenov/etal/2014b	Mladenov, Martin and Globerson, Amir and Kersting, Kristian. Lifted Message Passing as Reparametrization of Graphical Models. In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI), 2014.
Natarajan/etal/2014a	Natarajan, Sriraam and Picado Leiva, Jose Manuel and Khot, Tushar and Kersting, Kristian and Re, Christopher and Shavlik, Jude. Effectively creating weakly labeled training examples via approximate domain knowledge. In Ramon, Jan and Davis, Jesse (editors), Proceedings of the 24th International Conference on Inductive Logic Programming (ILP), Springer, 2014.
Natarajan/Kersting/2014a	Natarajan, Sriraam and Kersting, Kristian and Khot, Tushar and Shavlik, Jude. Boosted Statistical Relational Learners: From Benchmarks to Data-Driven Medicine. Springer, 2014.
Neumann/etal/2014a	Neumann, Marion and Hallau, Lisa and Klatt, Benjamin and Kersting, Kristian and Bauckhage, Christian. Erosion Band Features for Cell Phone Image Based Plant Disease Classification. In Proceedings of the 22nd International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, IEEE, 2014.
Poole/etal/2014a	Poole, David and Buchman, David and Kazemi, Seyed Mehran and Kersting, Kristian and Natarajan, Sriraam. Population Size Extrapolation in Relational Probabilistic Modelling. In Proceedings of the 8th International Conference on Scalable Uncertainty Management (SUM), Springer, 2014.
Yang/etal/2014a	Yang, Shuo and Khot, Tushar and Kersting, Kristian and Kunapuli, Gautam and Hauser, Kris and Natarajan, Sriraam. Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach. In Kumar, Ravi and Toivonen, Hannu (editors), Proceedings of the IEEE International Conference on Data Mining (ICDM), IEEE, 2014.
Ahmadi/etal/2013a	Ahmadi, Babak and Kersting, Kristian and Mladenov, Martin and Natarajan, Sriraam. Exploiting Symmetries for Scaling Loopy Belief Propagation and Relational Training. In Machine Learning Journal, Vol. 92, No. 1, pages 91--132, Springer, 2013.
Bauckhage/etal/2013a	C. Bauckhage and K. Kersting and F. Hadiji. Mathematical Models of Fads Explain the Temporal Dynamics of Internet Memes. In Proceedings of the 7th International AAAI Conference on Weblogs and Social Media (ICWSM-2013), 2013.
Bauckhage/etal/2013b	Bauckhage, Christian and Kersting, Kristian and Rastegarpanah, Bashir. The Weibull as a Model of Shortest Path Distributions in Random Networks. In L. Adamic and L. Getoor and B. Huang and J. Leskovec and J. McAuley (editors), Working Notes of the International Workshop on Mining and Learning with Graphs, Chicago, IL, USA, 2013.
Bauckhage/Kersting/2013a	C. Bauckhage and K. Kersting. Data Mining and Pattern Recognition in Agriculture. In Kuenstliche Intelligenz (KI), Vol. 27, No. 4, pages 313--324, Springer, 2013.
Bauckhage/Kersting/2013b	C. Bauckhage and K. Kersting. Can Computers Learn from the Aesthetic Wisdom of the Crowd?. In Kuenstliche Intelligenz (KI), Vol. 27, No. 1, pages 25--35, Springer, 2013.
Fierens/etal/2013a	D. Fierens and K. Kersting and J. Davis and J. Chen and M. Mladenov. Pairwise Markov Logic. In F. Riguzzi, F. Zelezny (editors), Postproceedings of the 22nd International Conference on Inductive Logic Programming (ILP-2012), Springer, 2013.
Hadiji/Kersting/2013a	F. Hadiji and K. Kersting. Reduce and Re-Lift: Bootstrapped Lifted Likelihood Maximization for MAP. In Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13), 2013.
Khot/etal/2013a	T. Khot and S. Natarajan and K. Kersting and J. Shavlik. Learning Relational Probabilistic Models from Partially Observed Data -- Opening the Closed-World Assumption. In G. Zaverucha, V. Santos Costa (editors), In Post-Proceedings of the 23nd International Conference on Inductive Logic Programming (ILP-2013), Rio de Janeiro, Brazil, Srpinger, 2013.
Mahlein/Wahabzada/2013a	Mahlein, Anne-Katrin and Wahabzada, Mirwaes and Kersting, Kristian and Steiner, Ulrike and Oerke, Erich-Christian. Hyperspectral image analysis for automatic detection of plant diseases. In Proceedings of the 19. Workshop Computer-Bildanalyse in der Landwirtschaft und 2. Workshop Unbemannte autonom fliegende Systeme in der Landwirtschaft, erschienen in Bornimer Agrartechnische Berichte, Vol. 81, pages 154-158, 2013.
Natarajan/etal/2013b	S. Natarajan and K. Kersting and E. Ip and D. Jacobs and J. Carr. Early Prediction of Coronary Artery Calcification Levels Using Machine Learning. In Proceedings of 25th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-2013), AAAI, Bellevue, Washington, USA, AAAI Press, 2013.
Natarajan/etal/2013c	S. Natarajan and P. Odom and S. Joshi and T. Khot and K. Kersting and P. Tadepalli. Accelerating Imitation Learning in Relational Domains via Transfer by Initialization. In G. Zaverucha, V. Santos Costa (editors), In Post-Proceedings of the 23nd International Conference on Inductive Logic Programming (ILP-2013), Rio de Janeiro, Brazil, Springer, 2013.
Neumann/etal/2013a	M. Neumann and R. Garnett and K. Kersting. Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels. In Cheng Soon Ong and Tu Bao Ho (editors), Proceedings of the 5th Annual Asian Conference on Machine Learning (ACML 2013), Vol. 29, pages 357-372, 2013.
Neumann/etal/2013b	Neumann, Marion and Moreno, Plinio and Antanas, Laura and Garnett, Roman and Kersting, Kristian. Graph Kernels for Object Category Prediction in Task-Dependent Robot Grasping. In Adamic,L. and Getoor, L. and Huang, B. and Leskovec, J. and McAuley, J. (editors), Working Notes of the International Workshop on Mining and Learning with Graphs, Chicago, IL, USA, 2013.
Ahmadi/etal/2012a	B. Ahmadi and K. Kersting and S. Natarajan. Lifted Online Training of Relational Models with Stochastic Gradient Methods. In P. Flach and T. De Bie and N. Cristianini (editors), Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2012), Vol. 7523, pages 585--600, Bristol, UK, Springer, 2012.
Ballvora/etal/2012a	A. Ballvora and C. Roemer and M. Wahabzada and U. Rascher and C. Thurau and C. Bauckhage and K. Kersting and L. Pluemer and J. Leon. Deep Phenotyping of Early Plant Response to Abiotic Stress Using Non--invasive Approaches in Barley. In Proceedings of the 11th International Barley Genetics Symposium (IBGS-2012), Hanhgzhou, China, Springer, 2012.
Bauckhage/etal/2012a	C. Bauckhage and K. Kersting and A. Schmidt. Agriculture´s Technological Makeover. In IEEE Pervasive Computing, Vol. 11, No. 2, pages 4--7, IEEE, 2012.
Bauckhage/etal/2012b	C. Bauckhage and K. Kersting and R. Sifa and C. Thurau and A. Drachen and A. Canossa. How Players Lose Interest in Playing a Game: An Empirical Study Based on Distributions of Total Playing Times. In S. Lucas and S.--B. Cho and M. S. Elnasr (editors), Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG), Granada, Spain, 2012.
Kersting/2012a	K. Kersting. Lifted Probabilistic Inference. In L. De Raedt and C. Bessiere and D. Dubois and P. Doherty and P. Frasconi and F. Heintz and P. Lucas (editors), Proceedings of 20th European Conference on Artificial Intelligence (ECAI--2012), ECCAI, Montpellier, France, IOS Press, 2012.
Kersting/etal/2012a	K. Kersting and M. Wahabzada and C. Roemer and C. Thurau and A. Ballvora and U. Rascher and J. Leon and C. Bauckhage and L. Pluemer. Simplex Distributions for Embedding Data Matrices over Time. In I. Davidson and C. Domeniconi (editors), Proceedings of the 12th SIAM International Conference on Data Mining (SDM 2012), Anaheim, CA, USA, 2012.
Kersting/etal/2012b	K. Kersting and C. Bauckhage and C. Thurau and M. Wahabzada. Matrix Factorization as Search. In P. Flach and T. De Bie and N. Cristianini (editors), Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Bristol, UK, Springer, 2012.
KKersting/etal/2012a	K.Kersting and Z. Xu and M. Wahabzada and C. Bauckhage and C. Thurau and C. Roemer and A. Ballvora and U. Rascher and J. Leon and L. Pluemer. Pre-symptomatic Prediction of Plant Drought Stress using Dirichlet-Aggregation Regression on Hyperspectral Images. In Twenty-Sixth Conference on Artificial Intelligence (AAAI-12), Toronto, Canada, 2012.
Lang/etal/2012a	T. Lang and M. Toussaint and K. Kersting. Exploration in Relational Domains for Model--based Reinforcement Learning. In Journal of Machine Learning Research (JMLR), Vol. 13, No. Dec, pages 3691--3734, 2012.
Mladenov/etal/2012a	Mladenov, Martin and Ahmad, Babaki and Kersting, Kristian. Lifted Linear Programming. In Proceedings of ths 15th International Conference on Artificial Intelligence and Statistics (AISTATS 2012), La Palma, Canary Islands, Spain, 2012.
Natarajan/etal/2012b	S. Natarajan and S. Joshi and B. Saha and A. Edwards and T. Khot and E. Moody and K. Kersting and C.T. Whitlow and J.A. Maldjian. A Machine Learning Pipeline for Three-way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain. In Proceedings of the 11th International Conference on Machine Learning and Applications (ICMLA), Boca Raton, Florida, USA, 2012.
Natarajan/etal/2012c	Natarajan, Sriraam and Khot, Tushar and Kersting, Kristian and Gutmann, Bernd and Shavlik, Jude. Gradient-based boosting for statistical relational learning: The relational dependency network case. In Machine Learning Journal, Vol. 86, No. 1, 2012.
Neumann/etal/2012a	M. Neumann and N. Patricia and R. Garnett and K. Kersting. Efficient Graph Kernels by Randomization. In P. Flach and T. De Bie and N. Cristianini (editors), Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2012), Bristol, UK, Springer, 2012.
Roemer/etal/2012a	C. Roemer and M. Wahabzada and A. Ballvora and F. Pinto and M. Rossini and C. Panigada and J. Behmann and J. Leon and C. Thurau and C. Bauckhage and K. Kersting and U. Rascher and L. Pluemer. Early Drought Stress Detection in Cereals: Simplex Volume Maximization for Hyperspectral Image Analysis. In Functional Plant Biology, Vol. 39, pages 878-890, CSIRO Pblishing, 2012.
Schiegg/etal/2012a	M. Schiegg and M. Neumann and K. Kersting. Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data. In Proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS--12), La Palma, Canary Islands, Spain, 2012.
Thurau/etal/2012a	C. Thurau and K. Kersting and C. Bauckhage. Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study. In I. Davidson and C. Domeniconi (editors), Proceedings of the 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA, USA, 2012.
Wahabzada/etal/2012a	M. Wahabzada and K. Kersting and C. Bauckhage and C. Roemer and A. Ballvora and F. Pinto and U. Rascher and J.Leon and L. Pluemer. Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants. In de N. Freitas and K. Murphy (editors), Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI), Catalina Island, California, USA, 2012.
Xu/etal/2012a	Z. Xu and K. Kersting and C. Bauckhage. Efficiently Learning to Hash Proportional Data. In Proceedings of the IEEE Conference on Data Mining (ICDM-2012), Brussels, Belgium, IEEE, 2012.
Zamani/etal/2012a	Z. Zamani and S. Sanner and P. Poupart and K. Kersting. Symbolic Dynamic Programming for Continuous State and Observation POMDPs. In Advances in Neural Information Processing Systems 26 (NIPS-2012), Lake Tahoe, Nevada, USA, MIT Press, 2012.
Ahmadi/etal/2011a	B. Ahmadi and K. Kersting and S. Sanner. Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter. In T. Walsh (editors), Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), Barcelona, Spain, 2011.
Hadiji/etal/2011a	F. Hadiji and B. Ahmadi and K. Kersting. Efficient Sequential Clamping for Lifted Message Passing. In Proceedings of the 34th Annual German Conference on Artificial Intelligence (KI 2011), Vol. 7006, pages 122--133, Berlin, Springer, 2011.
Jawad/etal/2011a	A. Jawad and K. Kersting and N. Andrienko. Where Traffic meets DNA: Mobility Mining using Biological Sequence Analysis Revisited. In Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2011), Chicago, USA, 2011.
Joshi/etal/2011a	S. Joshi and K. Kersting and R. Khardon. Decision-Theoretic Planning with Generalized First Order Decision Diagrams. In Artificial Intelligence Journal (AIJ), Vol. 175, No. 18, pages 2198-2222, Elsevier, 2011.
Khot/etal/2011a	T. Khot and S. Natarajan and K. Kersting and J. Shavlik. Learning Markov Logic Networks via Functional Gradient Boosting. In Proceedings of the 2011 IEEE International Conference on Data Mining (ICDM), Vancouver, Canada, 2011.
Natarajan/etal/2011a	S. Natarajan and S. Joshi and P. Tadepelli and K. Kersting and J. Shavlik. Imitation Learning in Relational Worlds: A Functional Gradient Boosting Approach. In T. Walsh (editors), Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), Barcelona, Spain, 2011.
Neumann/etal/2011a	M. Neumann and K. Kersting and B. Ahmadi. Markov Logic Sets: Towards Lifted Information Retrieval using PageRank and Label Propagation. In W. Burgard and D. Roth (editors), Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2011), San Francisco, CA, USA, AAAI Press, 2011.
Thurau/etal/2011a	Thurau, Christian and Kersting, Kristian and Wahabzada, Mirwaes and Bauckhage, Christian. Descriptive Matrix Factorization for Sustainability -- Adopting the Principle of Opposites. In Data Mining and Knowledge Discovery, Vol. 24, No. 2, pages 325-354, Springer, 2011.
Thurau/etal/2011b	C. Thurau and K. Kersting and M. Wahabzada and C. Bauckhage. Convex Non-negative Matrix Factorization for Massive Datasets. In Knowledge and Information Systems (KAIS), Vol. 29, No. 2, pages 457-478, Springer, 2011.
Wahabzada/etal/2011a	M. Wahabzada and K. Kersting and C. Bauckhage and A. Pilz. More Influence Means Less Work: Fast Latent Dirichlet Allocation by Influence Scheduling. In Proceedings of 20th ACM Conference on Information and Knowledge Management (CIKM 2012), Glasgow, UK, 2011.
Wahabzada/Kersting/2011a	M. Wahabzada and K. Kersting. Larger Residuals, Less Work: Active Document Scheduling for Latent Dirichlet Allocation. In D. Gunopulos and T. Hofmanm and D. Malerba and M. Vazirgiannis (editors), Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2011), pages 475-490, Springer, 2011.
Xu/Kersting/2011a	Z. Xu and K. Kersting. Multi-Task Learning with Task Relations. In Proc. of the 2011 IEEE International Conference on Data Mining (ICDM), Vancouver, Canada, 2011.
Kersting/etal/2010a	Kersting, Kristian and El Massaoudi, Youssef and Ahmadi, Babak and Hadiji, Fabian. Informed Lifting for Message-Passing. In Fox, M. and Poole, D. (editors), Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), Atlanta, USA, 2010.
Sanner/Kersting/2010a	Sanner, Scott and Kersting, Kristian. Symbolic Dynamic Programming for First-order POMDPs. In Fox, M. and Poole, D. (editors), Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), Atlanta, USA, 2010.
Katz/etal/2008a	Katz, Yarden and Goodman, Noah D. and Kersting, Kristian and Kemp, Charles and Tenenbaum, Josh. Modeling Semantic Cognition as Logical Dimensionality Reduction. In Proceedings of the Thirtieth Annual Conference of the Cognitive Science Society (CogSci), 2008.
Kersting/Driessens/2008a	Kersting, Kristian and Driessens, Kurt. Non-Parametric Policy Gradients: A Unified Treatment of Propositional and Relational Domains. In McCallum, A. and Roweis, S. (editors), Proceedings of the 25th International Conference on Machine Learning, Helsinki, Finland, 2008.
Milch/etal/2008a	Milch, Brian and Zettlemoyer, Luke S. and Kersting, Kristian and Haimes, Michael and Kaelbling, Leslie Pack. Lifted Probabilistic Inference with Counting Formulas. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, Chicago, Illinois, 2008.
Raedt/etal/2008a	L. De Raedt and K. Kersting and A. Kimmig and K. Revoredo and H. Toivonen. Compressing Probabilistic Prolog Programs. In Machine Learning Journal (MLJ), Vol. 70,, No. 2-3, pages 151--168, Springer, 2008.
Kersting/etal/2007a	Kersting, Kristian and Plagemann, Christian and Pfaff, Patrick and Burgard, Wolfram. Most Likely Heteroscedastic Gaussian Process Regression. In Ghahramani, Z. (editors), Proceedings of the 24th Annual International Conference on Machine Learning, Corvallis, OR, USA, 2007.
Landwehr/etal/2007a	N. Landwehr and K. Kersting and L. De Raedt. nFOIL: Integrating Naive Bayes and FOIL. In Journal of Machine Learning Research (JMLR), Vol. 8, pages 481--507, 2007.
Kersting/2006a	Kersting, Kristian. An Inductive Logic Programming Approach to Statistical Relational Learning. In AI Communications, Vol. 19, No. 4, pages 389--390, 2006.
Kersting/etal/2006a	K. Kersting and L. De Raedt and T. Raiko. Logical Hidden Markov Models. In Journal of Artificial Intelligence Research (JAIR), Vol. 25, pages 425--456, 2006.
Raedt/Kersting/2003a	L. De Raedt and K. Kersting. Probabilistic Logic Learning. In S. Dzeroski and L. De Raedt (editors), ACM SIGKDD Explorations, Vol. 5, No. 1, pages 31--48, 2003.
Ganzert/etal/2002a	S. Ganzert and J. Guttmann and K. Kersting and R. Kuhlen and C. Putensen and M. Sydow and S. Kramer. Analysis of Respiratory Pressure-Volume Curves in Intensive Care Medicine Using Inductive Machine Learning. In Artificial Intelligence in Medicine, Vol. 26, No. 1-2, pages 69--86, 2002.

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