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Kristian Kersting

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ObjectID : Author/520160
Kristian Kersting
(Publications: 78)
(Citation Count: 451)
(G-Index: 19)
(H-Index: 11)
HomePage
D-79085 Freiburg i. Brg . , Germany
University of Freiburg, Freiburg, Germany
Permanent Link: http://academic.research.microsoft.com/Author/520160.aspx
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Year 2009
Zhao Xu, Kristian Kersting, Volker Tresp :
Multi-Relational Learning with Gaussian Processes
, IJCAI
, 2009
(Citations: 3)
Novi Quadrianto, Kristian Kersting, Mark D. Reid, Tibério S. Caetano, Wray L. Buntine :
Kernel Conditional Quantile Estimation via Reduction Revisited
, ICDM
, 2009
Marion Neumann, Kristian Kersting, Zhao Xu, Daniel Schulz :
Stacked Gaussian Process Learning
, ICDM
, 2009
Saket Joshi, Kristian Kersting, Roni Khardon :
Generalized First Order Decision Diagrams for First Order Markov Decision Processes
, IJCAI
, 2009
Christian Thurau, Kristian Kersting, Christian Bauckhage :
Convex Non-negative Matrix Factorization in the Wild
, ICDM
, 2009
Kristian Kersting, Zhao Xu :
Learning Preferences with Hidden Common Cause Relations
, PKDD
, 2009
Year 2008
Brian Milch, Luke S. Zettlemoyer, Kristian Kersting, Michael Haimes, Leslie Pack Kaelbling :
Lifted Probabilistic Inference with Counting Formulas
, AAAI
, 2008
(Citations: 7)
Luc De Raedt, Kristian Kersting :
Probabilistic Inductive Logic Programming
, ILP
, 2008
(Citations: 5)
Christian Plagemann, Kristian Kersting, Wolfram Burgard :
Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness
, PKDD
, 2008
(Citations: 4)
Kristian Kersting, Luc De Raedt :
Basic Principles of Learning Bayesian Logic Programs
, ILP
, 2008
(Citations: 2)
Christian Plagemann, Sebastian Mischke, Sam Prentice, Kristian Kersting, Nicholas Roy, Wolfram Burgard :
Learning predictive terrain models for legged robot locomotion
, 2008
(Citations: 2)
Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen :
Compressing probabilistic Prolog programs
, ML
, 2008
(Citations: 1)
Kristian Kersting, Luc De Raedt, Bernd Gutmann, Andreas Karwath, Niels Landwehr :
Relational Sequence Learning
, ILP
, 2008
(Citations: 1)
Bernd Gutmann, Angelika Kimmig, Kristian Kersting, Luc De Raedt :
Parameter Learning in Probabilistic Databases: A Least Squares Approach
, PKDD
, 2008
(Citations: 1)
Kristian Kersting, Kurt Driessens :
Non-parametric policy gradients: a unified treatment of propositional and relational domains
, ICML
, 2008
(Citations: 1)
Sriraam Natarajan, Hung H. Bui, Prasad Tadepalli, Kristian Kersting, Weng-keen Wong :
Logical Hierarchical Hidden Markov Models for Modeling User Activities
, ILP
, 2008
(Citations: 2)
Olana Missura, Kristian Kersting, Thomas Gärtner :
Towards Engaging Games
, LWA
, 2008
Andreas Karwath, Kristian Kersting, Niels Landwehr :
Boosting Relational Sequence Alignments
, ICDM
, 2008
Kristian Kersting :
SRL without Tears: An ILP Perspective
, ILP
, 2008
Year 2007
Kristian Kersting, Christian Plagemann, Patrick Pfaff, Wolfram Burgard :
Most likely heteroscedastic Gaussian process regression
, ICML
, 2007
(Citations: 6)
Christian Plagemann, Kristian Kersting, Patrick Pfaff, Wolfram Burgard :
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders
, RSS
, 2007
(Citations: 6)
Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen Muggleton :
07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis
, Dagstuhl Seminars
, 2007
Year 2006
Kristian Kersting, Luc De Raedt, Tapani Raiko :
Logical Hidden Markov Models
, JAIR
, 2006
(Citations: 18)
Bernd Gutmann, Kristian Kersting :
TildeCRF: Conditional Random Fields for Logical Sequences
, ECML
, 2006
(Citations: 10)
Rudolph Triebel, Kristian Kersting, Wolfram Burgard :
Robust 3D Scan Point Classification using Associative Markov Networks
, ICRA
, 2006
(Citations: 7)
Alexandru Cocora, Kristian Kersting, Christian Plagemann, Wolfram Burgard, Luc De Raedt :
Learning Relational Navigation Policies
, 2006
(Citations: 5)
Kristian Kersting :
An inductive logic programming approach to statistical relational learning
, AICOM
, 2006
(Citations: 3)
Uwe Dick, Kristian Kersting :
Fisher Kernels for Relational Data
, ECML
, 2006
(Citations: 1)
Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen :
Revising Probabilistic Prolog Programs
, ILP
, 2006
Andreas Karwath, Kristian Kersting :
Relational Sequence Alignments and Logos
, ILP
, 2006
K. Kersting, A. Karwath :
On Relational Sequence Alignments and Their Infor-mation Content
, 2006
Year 2005
Kristian Kersting, Tapani Raiko :
"Say EM" for Selecting Probabilistic Models for Logical Sequences
, UAI
, 2005
(Citations: 10)
Niels Landwehr, Kristian Kersting, Luc De Raedt :
nFOIL: Integrating Naïve Bayes and FOIL
, AAAI
, 2005
(Citations: 10)
Luc De Raedt, Kristian Kersting, Sunna Torge :
Towards Learning Stochastic Logic Programs from Proof-Banks
, AAAI
, 2005
(Citations: 5)
Year 2004
Kristian Kersting, Martijn Van Otterlo, Luc De Raedt :
Bellman goes relational
, ICML
, 2004
(Citations: 30)
Luc De Raedt, Kristian Kersting :
Probabilistic Inductive Logic Programming
, ALT
, 2004
(Citations: 19)
Kristian Kersting, Luc De Raedt :
Logical Markov Decision Programs and the Convergence of Logical TD(lambda)
, ILP
, 2004
(Citations: 3)
Kristian Kersting, Uwe Dick :
Balios - The Engine for Bayesian Logic Programs
, PKDD
, 2004
(Citations: 4)
Kristian Kersting, Thomas Gärtner :
Fisher Kernels for Logical Sequences
, ECML
, 2004
Year 2003
Luc De Raedt, Kristian Kersting :
Probabilistic logic learning
, SIGKDD Explorations
, 2003
(Citations: 43)
Kristian Kersting, Tapani Raiko, Stefan Kramer, Luc De Raedt :
Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models
, Pacific Symposium on Biocomputing
, 2003
(Citations: 11)
Kristian Kersting, Luc De Raedt :
Logical Markov Decision Programs
, 2003
(Citations: 8)
Kristian Kersting, Tapani Raiko, Stefan Kramer, Luc De Raedt :
Towards Discovering Structural Signatures of Protein Folds based on
, Pacific Symposium on Biocomputing
, 2003
(Citations: 8)
K. Kersting, T. Raiko, L. De Raedt :
A Struc-tural GEM for Learning Logical Hidden Markov Mod-els
, 2003
(Citations: 4)
L. De Raedt, K. Kersting :
ACM-SIGKDD Ex-plorations: Special issue on Multi-Relational Data Mining
, 2003
(Citations: 5)
Jörg Fischer, Kristian Kersting :
Scaled CGEM: A Fast Accelerated EM
, ECML
, 2003
(Citations: 5)
Year 2002
Kristian Kersting, Luc De Raedt :
Basic Principles of Learning Bayesian Logic Programs
, 2002
(Citations: 20)
Steven Ganzert, Josef Guttmann, Kristian Kersting, Ralf Kuhlen, Christian Putensen, Michael Sydow, Stefan Kramer :
Analysis of respiratory pressure-volume curves in intensive care medicine using inductive machine learning
, ARTMED
, 2002
(Citations: 6)
Kristian Kersting, Tapani Raiko, Luc De Raedt :
Logical Hidden Markov Models (Extendes abstract)
, PGM
, 2002
(Citations: 2)
Kristian Kersting, Niels Landwehr :
Scaled Conjugate Gradients for Maximum Likelihood: An Empirical Comparison with the EM Algorithm
, PGM
, 2002
(Citations: 1)
Steven Ganzert, Josef Guttmann, Kristian Kersting, Ralf Kuhlen, Christian Putensen, Michael Sydow, Stefan Kramer :
Analysis of Respiratory Pressure-Volume Curves in
, ARTMED
, 2002
Year 2001
Kristian Kersting, Luc De Raedt :
Towards Combining Inductive Logic Programming with Bayesian Networks
, ILP
, 2001
(Citations: 30)
Kristian Kersting, Luc De Raedt :
Adaptive Bayesian Logic Programs
, ILP
, 2001
(Citations: 20)
Kristian Kersting, Luc De Raedt :
Bayesian Logic Programs
, CORR
, 2001
(Citations: 22)
Year 2000
Kristian Kersting, Luc De Raedt :
Bayesian Logic Programs
, ILP
, 2000
(Citations: 70)
Kristian Kersting, Luc De Raedt, Stefan Kramer :
Interpreting Bayesian Logic Programs
, 2000
(Citations: 13)
Year Unknown
Kristian Kersting, Luc De Raedt :
Logical Markov Decision Programs and the Convergence of Logical TD
(Citations: 6)
Kristian Kersting, Bernd Gutmann :
Unbiased Conjugate Direction Boosting for Conditional Random Fields
(Citations: 2)
Niels Landwehr, Kristian Kersting, Luc De Raedt :
Integrating Na¨ıve Bayes and FOIL
(Citations: 3)
Ingo Thon, Kristian Kersting :
Distributed Relational State Representations for Complex Stochastic Processes
(Citations: 1)
Kristian Kersting :
Representational Power of Probabilistic-Logical Models: From Upgrading to Downgrading
(Citations: 2)
Bernd Gutmann, Kristian Kersting :
Stratified Gradient Boosting for Fast Training of Conditional Random Fields
(Citations: 1)
Martijn Van Otterlo, Kristian Kersting, Luc De Raedt :
Bellman goes Relational (Extended Abstract)
(Citations: 1)
T. Raiko, K. Kersting, J. Karhunen, L. De Raedt :
Bayesian Learning of Logical Hidden Markov Models
(Citations: 1)
Kristian Kersting, Brian Milch, Luke S. Zettlemoyer, Michael Haimes, Leslie Pack Kaelbling :
Reasoning about Large Populations with Lifted Probabilistic Inference
Steven Ganzert, Knut Moller, Kristian Kersting, Luc De Raedt, Josef Guttmann :
Equation Discovery for Model Identification in Respiratory Mechanics under Conditions of Mechanical Ventilation
Yarden Katz, Noah D. Goodman, Kristian Kersting, Charles Kemp, Joshua B. Tenenbaum :
Modeling Semantic Cognition as Logical Dimensionality Reduction
Steven Ganzert, Knut Möller, Stefan Kramer, Kristian Kersting, Josef Guttmann :
Identifying Mathematical Models of the Mechanically Ventilated Lung Using Equation Discovery
Tayfun G Urel, Kristian Kersting :
On the Trade-Off Between Iterative Classication and Collective Classication: First Experimental Results
Zhao Xu, Volker Tresp, Achim Rettinger, Kristian Kersting :
Social Network Mining with Nonparametric Relational Models
Christian Plagemann, Kristian Kersting, Patrick Pfaff, Wolfram Burgard :
Heteroscedastic Gaussian Process Regression for Modeling Range Sensors in Mobile Robotics
Zhao Xu, Kristian Kersting, Fraunhofer Iais, Volker Tresp :
Gaussian Process Models for Colored Graphs
Manfred Jaeger, Kristian Kersting :
Expressivity Analysis for PL-Languages
Kristian Kersting, Luc De Raedt :
1 Bayesian Logic Programming
Kristian Kersting, Luc De Raedt :
Software Tools for Probabilistic Inductive Logic Programming
Bernd Gutmann, Kristian Kersting :
Stratified Gradient Boosting for Fast Training of CRFs (Extended Abstract)
Ingo Thon, Kristian Kersting :
Distributed Relational State Representations for Complex Stochastic Processes (Extended Abstract)
Kristian Kersting, Zhao Xu :
Relational Gaussian Processes for Learning Preference Relations
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