|
Email:
kristian.kersting
cs.tu-dortmund.de
Telefon: Telefax: 0231/755-5105 Raumnummer: Bild Reprovorlage |
Seit dem 1. Mai 2017 bin ich an der TU Darmstadt, aber zur Zeit gebe ich auch noch einen Kurs an der TU Dortmund.
Kristian Kersting hat an der Universität Freiburg Informatik studiert und dort 2006 mit einer Arbeit zum statistisch-relationalem Data Mining promoviert. Nach einem PostDoc-Aufenthalt am MIT, USA, wurde er 2008 in das Fraunhofer ATTRACT aufgenommen, um eine Nachwuchsforschergruppe am Fraunhofer IAIS, Sankt Augustin, aufzubauen. Parallel war er Dozent an der Universität Bonn, an der er 2012 zum W1-Professor für raum-zeitliche Muster in der Landwirtschaft berufen wurde. Im selben Jahre nahm er auch eine Adjunct Assistant Professorship an der Medical School der Wake-Forest University, USA, wahr. 2013 folgte er einem Ruf der Technischen Universität Dortmund auf eine W2-Professur für Data Mining. Interaktiver CV
Sein Forschungsgebiet betrifft die effiziente Wissensentdeckung in großen, komplexen und unsicheren Datenmengen, mit deren Methoden er unter anderem Anwendungen in der Medizin, der Phänotypisierung von Pflanzen, der Verkehrsprognose und des kollektiven Verhaltens von Menschen angeht. Neben zahlreichen Herausgeber- (z.B. JAIR, AIJ, DAMI und MLJ) und Fachgutachtertätigkeiten leitete er 2013 gemeinsam mit Hendrik Blockeel, Siegfried Nijssen und Filip Zelezny die international zweitbeliebteste Konferenz im Bereich Maschinelles Lernen und Data Mining, die ECML PKDD sowie mehrere internationale Workshops wie z.B. SymInfOpt, BeyondLabeler, BUDA, CMPL, CoLISD, MLG und SRL und auch den AAAI Student Abstract Track und das Starting AI Research Symposium (STAIRS). Zusammen mit Jure Leskovec (Stanford) leitete er 2015 das Best Paper Award Committee der KDD, die international beliebteste Konferenz im Bereich Data Mining. Zusammen mit Stuart Russell (Berkeley), Leslie Kaelbling (MIT), Alon Halevy (Goolge), Sriraam Natarajan (Indiana) und Lilyana Mihalkova (Google) hat er den Internationalen Workshop on Statistical Relational AI begründet. In 2017 wird er zusammen mit Gal Elidan die UAI leiten, eine der wichtigsten internationalen Konferenzen zur Wissensrepräsentation, zum Lernen und zum Schlussfolgern unter Unsicherheit. Seine Arbeiten und für seine Tätigkeiten hat er eine Reihe von Auszeichnungen erhalten, etwa
2009 war er ein ERCIM Cor Baayen Award 2009 Finalist.
Software und ähnliche Dinge befinden sich in unserem Web Lab.
Publikationen (siehe weiter untern) können auch auf loop, DBLP, SemanticScholar und GOOGLE Scholar Citations gefunden werden.
| 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.
Folien unseres IJCAI 2016 Tutorials |
|
| 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 |
Elena Erdmann, Martin Mladenov, Alejandro Molina
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)
Interview@MLconf 2016 und auch das 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 , "Algorithmen — Wer kontrolliert "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
"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 auf 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),
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
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), MOD'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)
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.
"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 Jahre künstliche Intelligenz – Wo ist sie? Sommerakademie der Studienstiftung des deutschen Volkes 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
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pflegix.de, seit 2016. |
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heydeal.de, seit 2016. |
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goedle.io, seit 2015. |
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ABIDA - ASSESING BIG DATA, seit 2015. |
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GameAnalytics, 2012-2014. |
bla
| 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.
|
| 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.
|
| 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), Seiten 2357--2363, 2017. |
| Kersting/etal/2017 |
Kersting, Kristian and Mladenov, Martin and Tokmakov, Pavel.
Relational Linear Programming.
In
Artificial Intelligence Journal (AIJ),
Vol. 244,
Seiten 188-216,
2017.
|
| 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, Seiten 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,
Seiten 134-150,
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. |
| 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.
|
| 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, Seiten 1-136, 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), Seiten 1095--1100, 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,
Seiten 282,
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, Seiten 1-9, 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.
|
| 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. |
| 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.
|
| 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. |
| 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,
Seiten 579-589,
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.
|
| 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.
|
| 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,
Seiten 491-498,
Springer,
2016.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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. |
| 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.
|
| 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.
|
| 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.
|
| 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, Seiten 477-507, 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.
|
| 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.
|
| Kersting/Natarajan/2015a |
Kersting, Kristian and Natarajan, Sriraam.
Statistical Relational Artificial Intelligence: From Distributions through Actions to Optimization.
In
Künstliche Intelligenz,
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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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),
Seiten 881--886,
IEEE,
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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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
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