PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Kristian Kersting

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Number of EPrints submitted by this user: 32

A Bayesian regression approach to terrain mapping and an application to legged robot locomotion
Christian Plagemann, Sebastian Mischke, Sam Prentice, Kristian Kersting, Nicholas Roy and Wolfram Burgard
Journal of Field Robotics Volume 26, Number 10, pp. 789-811, 2009.

Multi-Relational Learning with Gaussian Processes
Zhao Xu, Kristian Kersting and Volker tresp
In: IJCAI 2009, 11-17 Jul 2009, Passadena, USA.

Generalized First Order Decision Diagrams for First Order Markov Decision Processes
Saket Joshi, Kristian Kersting and Roni Khardon
In: IJCAI 2009, 11-17 Jul 2009, Passadena, USA.

Convex Non-negative Matrix Factorization in the Wild
Christian Thurau, Kristian Kersting and Christian Bauckhage
In: ICDM 2009, 06-09 Dec 2009, Miami, USA.

Stacked Gaussian Process Learning
Marion Neumann, Kristian Kersting, Zhao Xu and Daniel Schulz
In: ICDM 2009, 06-09 Dec 2009, Miami, USA.

Counting Belief Propagation
Kristian Kersting, Babak Ahmadi and Sriraam Natarajan
In: UAI 2009, 18-21 Jul 2009, Montreal, Canad.

ILP, the Blind, and the Elephant: Euclidean Embedding of Co-Proven Queries
Hannes Schulz, Kristian Kersting and Andreas Karwath
In: ILP 2009, 02-04 July 2009, Leuven, Belgium.

Identifying Mathematical Models of the Mechanically Ventilated Lung Using Equation Discovery
Steven Ganzert, Knut Moeller, Stefan Kramer, Kristian Kersting and Josef Guttmann
In: 11th Conference on Medical Physics and Biomedical Engineering (WC 2009), 07-12 Sep 2009, Munich, Germany.

Learning Preferences with Hidden Common Cause Relations
Kristian Kersting and Zhao Xu
In: ECML-PKDD 2009, 07-11 Sep 2009, Bled, Slovenia.

Descriptive matrix factorization for sustainability: Adopting the principle of opposites
Christian Thurau, Kristian Kersting, Mirwaes Wahabzada and Christian Bauckhage
Data Mining and Knowledge Discovery Volume 24, Number 2, pp. 325-354, 2011.

Gradient-based boosting for statistical relational learning: The relational dependency network case
Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann and Jude Shavlik
Machine Learning Volume 86, Number 1, pp. 25-56, 2011.

Decision-theoretic planning with generalized first-order decision diagrams
Saket Joshi, Kristian Kersting and Roni Khardon
Artificial Intelligence Volume 175, Number 18, pp. 2198-2222, 2011.

Perception beyond the here and now
Albrecht Schmidt, Marc Langheinrich and Kristian Kersting
IEEE Computer Volume 44, Number 2, pp. 86-88, 2011.

Convex non-negative matrix factorization for massive datasets
Christian Thurau, Kristian Kersting, Mirwaes Wahabzada and Christian Bauckhage
Knowledge Information Systems Volume 29, Number 2, pp. 457-478, 2010.

Symbolic Dynamic Programming for First-order POMDPs
Scott Sanner and Kristian Kersting
In: AAAI 2010(2010).

Informed Lifting for Message-Passing
Kristian Kersting, Youssef El Massaoudi, Fabian Hadiji and Babak Ahmadi
In: AAAI 2010(2010).

Yes we can: simplex volume maximization for descriptive web-scale matrix factorization
Christian Thurau, Kristian Kersting and Christian Bauckhage
In: CIKM 2010(2010).

Topic Models Conditioned on Relations
Mirwaes Wahabzada, Zhao Xu and Kristian Kersting
In: ECML PKDD 2010(2010).

Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes
Zhao Xu, Kristian Kersting and Thorsten Joachims
In: ECML PKDD 2010(0210).

Larger Residuals, Less Work: Active Document Scheduling for Latent Dirichlet Allocation
Mirwaes Wahabzada and Kristian Kersting
In: ECML PKDD 2011(2011).

Multi-task Learning with Task Relations
Zhao Xu and Kristian Kersting
In: ICDM 2011(2011).

Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter
Babak Ahmadi, Kristian Kersting and Scott Sanner
In: IJCAI 2011(2011).

Can Computers Learn from the Aesthetic Wisdom of the Crowd?
Christian Bauckhage and Kristian Kersting
Künstliche Intelligenz Volume 27, Number 1, pp. 25-35, 2013.

Descriptive matrix factorization for sustainability: Adopting the principle of opposites.
Christian Thurau, Kristian Kersting, Mirwaes Wahabzada and Christian Bauckhage
Data Mining and Knowledge Discovery Volume 24, Number 2, pp. 325-354, 2012.

Gradient-based boosting for statistical relational learning: The relational dependency network case
Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann and Jude Shavlik
Machine Learning Volume 86, Number 1, pp. 25-56, 2012.

Agriculture's Technological Makeover
Christian Bauckhage, Kristian Kersting and Albrecht Schmidt
IEEE Pervasive Computing Volume 11, Number 2, pp. 4-7, 2012.

Lifted Linear Programming
Martin Mladenov, Babak Ahamadi and Kristian Kersting
In: Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS)(2012).

Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data
Martin Schiegg, Marion Neumann and Kristian Kersting
In: Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS)(2012).

Efficient Learning for Hashing Proportional Data
Zhao Xu, Kristian Kersting and Christian Bauckhage
In: 12th IEEE International Conference on Data Mining (ICDM)(2102).

Symbolic Dynamic Programming for Continuous State and Observation POMDPs
Zahra Zamani, Scott Sanner, Pascal Poupart and Kristian Kersting
In: NIPS 2012(2012).

Efficient Graph Kernels by Randomization
Marion Neumann, Novi Patricia, Roman Garnett and Kristian Kersting
In: ECMLPKDD 2012(2012).

Lifted Online Training of Relational Models with Stochastic Gradient Methods
Babak Ahamadi, Kristian Kersting and Sriraam Natarajan
In: ECMLPKDD 2012(2012).