Kristian Kersting

According to our database1, Kristian Kersting authored at least 212 papers between 2000 and 2019.

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Bibliography

2019
Extending Hyperspectral Imaging for Plant Phenotyping to the UV-Range.
Remote Sensing, 2019

Editorial: Statistical Relational Artificial Intelligence.
Front. Robotics and AI, 2019

Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach.
Auton. Robots, 2019

Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Gaussian Lifted Marginal Filtering.
Proceedings of the KI 2019: Advances in Artificial Intelligence, 2019

Faster Attend-Infer-Repeat with Tractable Probabilistic Models.
Proceedings of the 36th International Conference on Machine Learning, 2019

Explanatory Interactive Machine Learning.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Semantics Derived Automatically from Language Corpora Contain Human-like Moral Choices.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Automatic Bayesian Density Analysis.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
From Big Data to Big Artificial Intelligence? - Algorithmic Challenges and Opportunities of Big Data.
KI, 2018

Making AI Smarter.
KI, 2018

Structure Learning for Relational Logistic Regression: An Ensemble Approach.
Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Sixteenth International Conference, 2018

Lifted Filtering via Exchangeable Decomposition.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Systems AI: A Declarative Learning Based Programming Perspective.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Efficient Symbolic Integration for Probabilistic Inference.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Automatic Mapping of the Sum-Product Network Inference Problem to FPGA-Based Accelerators.
Proceedings of the 36th IEEE International Conference on Computer Design, 2018

Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Core Dependency Networks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Symbolic Dynamic Programming.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Statistical Relational Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Gaussian Process.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Statistical Relational Learning of Grammar Rules for 3D Building Reconstruction.
Trans. GIS, 2017

Semantic Interpretation of Multi-Modal Human-Behaviour Data - Making Sense of Events, Activities, Processes.
KI, 2017

Relational linear programming.
Artif. Intell., 2017

Graph Enhanced Memory Networks for Sentiment Analysis.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach.
Proceedings of the Inductive Logic Programming - 27th International Conference, 2017

Stochastic Online Anomaly Analysis for Streaming Time Series.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Glocalized Weisfeiler-Lehman Graph Kernels: Global-Local Feature Maps of Graphs.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Interactive Data Analytics for the Humanities.
Proceedings of the Computational Linguistics and Intelligent Text Processing, 2017

Modeling heart procedures from EHRs: An application of exponential families.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Lifted Inference for Convex Quadratic Programs.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

The Symbolic Interior Point Method.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Statistical Relational Artificial Intelligence: Logic, Probability, and Computation
Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, 2016

Feeding the World with Big Data: Uncovering Spectral Characteristics and Dynamics of Stressed Plants.
Proceedings of the Computational Sustainability, 2016

Propagation kernels: efficient graph kernels from propagated information.
Machine Learning, 2016

Collective Attention on the Web.
Foundations and Trends in Web Science, 2016

How Is a Data-Driven Approach Better than Random Choice in Label Space Division for Multi-Label Classification?
Entropy, 2016

Scaling Lifted Probabilistic Inference and Learning Via Graph Databases.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Learning Through Advice-Seeking via Transfer.
Proceedings of the Inductive Logic Programming - 26th International Conference, 2016

Learning Using Unselected Features (LUFe).
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Faster Kernels for Graphs with Continuous Attributes via Hashing.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Deep Distant Supervision: Learning Statistical Relational Models for Weak Supervision in Natural Language Extraction.
Proceedings of the Solving Large Scale Learning Tasks. Challenges and Algorithms, 2016

Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

RELOOP: A Python-Embedded Declarative Language for Relational Optimization.
Proceedings of the Declarative Learning Based Programming, 2016

2015
Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases.
Machine Learning, 2015

Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data.
Machine Learning, 2015

Statistical Relational Artificial Intelligence: From Distributions through Actions to Optimization.
KI, 2015

pyGPs: a Python library for Gaussian process regression and classification.
J. Mach. Learn. Res., 2015

Automated interpretation of 3D laserscanned point clouds for plant organ segmentation.
BMC Bioinformatics, 2015

Reports of the AAAI 2014 Conference Workshops.
AI Magazine, 2015

LTE Connectivity and Vehicular Traffic Prediction Based on Machine Learning Approaches.
Proceedings of the IEEE 82nd Vehicular Technology Conference, 2015

Equitable Partitions of Concave Free Energies.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Parameterizing the Distance Distribution of Undirected Networks.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

How Viral Are Viral Videos?
Proceedings of the Ninth International Conference on Web and Social Media, 2015

Transfer Learning via Relational Type Matching.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Modeling Coronary Artery Calcification Levels from Behavioral Data in a Clinical Study.
Proceedings of the Artificial Intelligence in Medicine, 2015

Predicting Purchase Decisions in Mobile Free-to-Play Games.
Proceedings of the Eleventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2015

2014
Boosted Statistical Relational Learners - From Benchmarks to Data-Driven Medicine
Springer Briefs in Computer Science, Springer, ISBN: 978-3-319-13644-8, 2014

Relational learning helps in three-way classification of Alzheimer patients from structural magnetic resonance images of the brain.
Int. J. Machine Learning & Cybernetics, 2014

Künstliche Intelligenz für Computerspiele - Historische Entwicklung und aktuelle Trends.
Informatik Spektrum, 2014

Collective attention to social media evolves according to diffusion models.
Proceedings of the 23rd International World Wide Web Conference, 2014

Lifted Message Passing as Reparametrization of Graphical Models.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Population Size Extrapolation in Relational Probabilistic Modelling.
Proceedings of the Scalable Uncertainty Management - 8th International Conference, 2014

Mind the Nuisance: Gaussian Process Classification using Privileged Noise.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Relational Logistic Regression.
Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Fourteenth International Conference, 2014

Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge.
Proceedings of the Inductive Logic Programming - 24th International Conference, 2014

Erosion Band Features for Cell Phone Image Based Plant Disease Classification.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Explicit Versus Implicit Graph Feature Maps: A Computational Phase Transition for Walk Kernels.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Dimension Reduction via Colour Refinement.
Proceedings of the Algorithms - ESA 2014, 2014

Predicting player churn in the wild.
Proceedings of the 2014 IEEE Conference on Computational Intelligence and Games, 2014

Efficient Lifting of MAP LP Relaxations Using k-Locality.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

A Deeper Empirical Analysis of CBP Algorithm: Grounding Is the Bottleneck.
Proceedings of the Statistical Relational Artificial Intelligence, 2014

Power Iterated Color Refinement.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Relational Logistic Regression: The Directed Analog of Markov Logic Networks.
Proceedings of the Statistical Relational Artificial Intelligence, 2014

Preface.
Proceedings of the Statistical Relational Artificial Intelligence, 2014

Lifting Relational MAP-LPs using Cluster Signatures.
Proceedings of the Statistical Relational Artificial Intelligence, 2014

Lifting Relational MAP-LPs Using Cluster Signatures.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track.
Machine Learning, 2013

Exploiting symmetries for scaling loopy belief propagation and relational training.
Machine Learning, 2013

Data Mining and Pattern Recognition in Agriculture.
KI, 2013

Can Computers Learn from the Aesthetic Wisdom of the Crowd?
KI, 2013

Guest editor's introduction: special issue of the ECML PKDD 2013 journal track.
Data Min. Knowl. Discov., 2013

The AAAI-13 Conference Workshops.
AI Magazine, 2013

Accelerating Imitation Learning in Relational Domains via Transfer by Initialization.
Proceedings of the Inductive Logic Programming - 23rd International Conference, 2013

Mathematical Models of Fads Explain the Temporal Dynamics of Internet Memes.
Proceedings of the Seventh International Conference on Weblogs and Social Media, 2013

Early Prediction of Coronary Artery Calcification Levels Using Machine Learning.
Proceedings of the Twenty-Fifth Innovative Applications of Artificial Intelligence Conference, 2013

Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels.
Proceedings of the Asian Conference on Machine Learning, 2013

Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text.
Proceedings of the Statistical Relational Artificial Intelligence, 2013

Lifted Inference via k-Locality.
Proceedings of the Statistical Relational Artificial Intelligence, 2013

Reduce and Re-Lift: Bootstrapped Lifted Likelihood Maximization for MAP.
Proceedings of the Statistical Relational Artificial Intelligence, 2013

Reduce and Re-Lift: Bootstrapped Lifted Likelihood Maximization for MAP.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

Preface.
Proceedings of the Statistical Relational Artificial Intelligence, 2013

MapReduce Lifting for Belief Propagation.
Proceedings of the Statistical Relational Artificial Intelligence, 2013

2012
Agriculture's Technological Makeover.
IEEE Pervasive Computing, 2012

Gradient-based boosting for statistical relational learning: The relational dependency network case.
Machine Learning, 2012

Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Lifted Linear Programming.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Exploration in relational domains for model-based reinforcement learning.
J. Mach. Learn. Res., 2012

Descriptive matrix factorization for sustainability Adopting the principle of opposites.
Data Min. Knowl. Discov., 2012

Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Deterministic CUR for Improved Large-Scale Data Analysis: An Empirical Study.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Simplex Distributions for Embedding Data Matrices over Time.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Efficient Graph Kernels by Randomization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Matrix Factorization as Search.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Lifted Online Training of Relational Models with Stochastic Gradient Methods.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Symbolic Dynamic Programming for Continuous State and Observation POMDPs.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Pairwise Markov Logic.
Proceedings of the Inductive Logic Programming - 22nd International Conference, 2012

A Machine Learning Pipeline for Three-Way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain.
Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

Efficient Learning for Hashing Proportional Data.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Lifted Probabilistic Inference.
Proceedings of the ECAI 2012, 2012

How players lose interest in playing a game: An empirical study based on distributions of total playing times.
Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games, 2012

Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning.
Machine Learning, 2011

Convex non-negative matrix factorization for massive datasets.
Knowl. Inf. Syst., 2011

Perception beyond the Here and Now.
IEEE Computer, 2011

Decision-theoretic planning with generalized first-order decision diagrams.
Artif. Intell., 2011

Larger Residuals, Less Work: Active Document Scheduling for Latent Dirichlet Allocation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Biological Sequence Analysis meets Mobility Mining.
Proceedings of the Report of the symposium "Lernen, 2011

O Scientist, Where Art Thou? Affiliation Propagation for Geo-Referencing Scientific Publications.
Proceedings of the Report of the symposium "Lernen, 2011

On Lifted PageRank, Kalman Filter and Towards Lifted Linear Program Solving.
Proceedings of the Report of the symposium "Lernen, 2011

Efficient Sequential Clamping for Lifted Message Passing.
Proceedings of the KI 2011: Advances in Artificial Intelligence, 2011

Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach.
Proceedings of the IJCAI 2011, 2011

Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter.
Proceedings of the IJCAI 2011, 2011

Multi-task Learning with Task Relations.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Learning Markov Logic Networks via Functional Gradient Boosting.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Where traffic meets DNA: mobility mining using biological sequence analysis revisited.
Proceedings of the 19th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems, 2011

Invited Talk: Increasing Representational Power and Scaling Inference in Reinforcement Learning.
Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

More influence means less work: fast latent dirichlet allocation by influence scheduling.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Symbolic Dynamic Programming.
Proceedings of the Encyclopedia of Machine Learning, 2010

Statistical Relational Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Gaussian Process.
Proceedings of the Encyclopedia of Machine Learning, 2010

Hierarchical Convex NMF for Clustering Massive Data.
Proceedings of the 2nd Asian Conference on Machine Learning, 2010

Reports of the AAAI 2010 Conference Workshops.
AI Magazine, 2010

Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Topic Models Conditioned on Relations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Exploration in Relational Worlds.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Beyond 2D-grids: a dependence maximization view on image browsing.
Proceedings of the 11th ACM SIGMM International Conference on Multimedia Information Retrieval, 2010

Convex NMF on Non-Convex Massiv Data.
Proceedings of the LWA 2010, 2010

Kernelized Map Matching for noisy trajectories.
Proceedings of the LWA 2010, 2010

Lifted Conditioning for Pairwise Marginals and Beyond.
Proceedings of the LWA 2010, 2010

Learning to hash logistic regression for fast 3D scan point classification.
Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

Multi-Agent Inverse Reinforcement Learning.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Kernelized map matching.
Proceedings of the 18th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems, 2010

Yes we can: simplex volume maximization for descriptive web-scale matrix factorization.
Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

Self-Taught Decision Theoretic Planning with First Order Decision Diagrams.
Proceedings of the 20th International Conference on Automated Planning and Scheduling, 2010

Symbolic Dynamic Programming for First-order POMDPs.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.
Proceedings of the Statistical Relational Artificial Intelligence, 2010

Informed Lifting for Message-Passing.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

Lifted Message Passing for Satisfiability.
Proceedings of the Statistical Relational Artificial Intelligence, 2010

Probabilistic Inductive Querying Using ProbLog.
Proceedings of the Inductive Databases and Constraint-Based Data Mining., 2010

2009
A Bayesian regression approach to terrain mapping and an application to legged robot locomotion.
J. Field Robotics, 2009

Counting Belief Propagation.
Proceedings of the UAI 2009, 2009

Learning Preferences with Hidden Common Cause Relations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

ILP, the Blind, and the Elephant: Euclidean Embedding of Co-proven Queries.
Proceedings of the Inductive Logic Programming, 19th International Conference, 2009

Multi-Relational Learning with Gaussian Processes.
Proceedings of the IJCAI 2009, 2009

Generalized First Order Decision Diagrams for First Order Markov Decision Processes.
Proceedings of the IJCAI 2009, 2009

Convex Non-negative Matrix Factorization in the Wild.
Proceedings of the ICDM 2009, 2009

Kernel Conditional Quantile Estimation via Reduction Revisited.
Proceedings of the ICDM 2009, 2009

Stacked Gaussian Process Learning.
Proceedings of the ICDM 2009, 2009

2008
Compressing probabilistic Prolog programs.
Machine Learning, 2008

Preface.
Ann. Math. Artif. Intell., 2008

Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Parameter Learning in Probabilistic Databases: A Least Squares Approach.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Towards Engaging Games.
Proceedings of the LWA 2008, 2008

Social Network Mining with Nonparametric Relational Models.
Proceedings of the Advances in Social Network Mining and Analysis, 2008

Learning predictive terrain models for legged robot locomotion.
Proceedings of the 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008

Logical Hierarchical Hidden Markov Models for Modeling User Activities.
Proceedings of the Inductive Logic Programming, 18th International Conference, 2008

Relational Sequence Learning.
Proceedings of the Probabilistic Inductive Logic Programming - Theory and Applications, 2008

Basic Principles of Learning Bayesian Logic Programs.
Proceedings of the Probabilistic Inductive Logic Programming - Theory and Applications, 2008

SRL without Tears: An ILP Perspective.
Proceedings of the Inductive Logic Programming, 18th International Conference, 2008

Non-parametric policy gradients: a unified treatment of propositional and relational domains.
Proceedings of the Machine Learning, 2008

Boosting Relational Sequence Alignments.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Lifted Probabilistic Inference with Counting Formulas.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Integrating Naïve Bayes and FOIL.
J. Mach. Learn. Res., 2007

Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders.
Proceedings of the Robotics: Science and Systems III, 2007

Most likely heteroscedastic Gaussian process regression.
Proceedings of the Machine Learning, 2007

07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

2006
Learning Relational Navigation Policies.
KI, 2006

Logical Hidden Markov Models.
J. Artif. Intell. Res., 2006

An inductive logic programming approach to statistical relational learning.
AI Commun., 2006

Learning Relational Navigation Policies.
Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006

Revising Probabilistic Prolog Programs.
Proceedings of the Inductive Logic Programming, 16th International Conference, 2006

Relational Sequence Alignments and Logos.
Proceedings of the Inductive Logic Programming, 16th International Conference, 2006

Robust 3D Scan Point Classification using Associative Markov Networks.
Proceedings of the 2006 IEEE International Conference on Robotics and Automation, 2006

TildeCRF: Conditional Random Fields for Logical Sequences.
Proceedings of the Machine Learning: ECML 2006, 2006

Fisher Kernels for Relational Data.
Proceedings of the Machine Learning: ECML 2006, 2006

2005
An Inductive Logic Programming Approach to Statistical Relational Learning
Frontiers in Artificial Intelligence and Applications 148, IOS Press, ISBN: 978-1-58603-674-4, 2005

"Say EM" for Selecting Probabilistic Models for Logical Sequences.
Proceedings of the UAI '05, 2005

Towards Learning Stochastic Logic Programs from Proof-Banks.
Proceedings of the Proceedings, 2005

nFOIL: Integrating Naïve Bayes and FOIL.
Proceedings of the Proceedings, 2005

2004
Balios - The Engine for Bayesian Logic Programs.
Proceedings of the Knowledge Discovery in Databases: PKDD 2004, 2004

Logical Markov Decision Programs and the Convergence of Logical TD(lambda).
Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

Bellman goes relational.
Proceedings of the Machine Learning, 2004

Fisher Kernels for Logical Sequences.
Proceedings of the Machine Learning: ECML 2004, 2004

Probabilistic Inductive Logic Programming.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2003
Probabilistic logic learning.
SIGKDD Explorations, 2003

Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models.
Proceedings of the 8th Pacific Symposium on Biocomputing, 2003

Scaled CGEM: A Fast Accelerated EM.
Proceedings of the Machine Learning: ECML 2003, 2003

2002
Analysis of respiratory pressure-volume curves in intensive care medicine using inductive machine learning.
Artificial Intelligence in Medicine, 2002

Logical Hidden Markov Models (Extendes abstract).
Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002

Scaled Conjugate Gradients for Maximum Likelihood: An Empirical Comparison with the EM Algorithm.
Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002

2001
Towards Combining Inductive Logic Programming with Bayesian Networks.
Proceedings of the Inductive Logic Programming, 11th International Conference, 2001

Adaptive Bayesian Logic Programs.
Proceedings of the Inductive Logic Programming, 11th International Conference, 2001

2000
Bayesian Logic Programs.
Proceedings of the Inductive Logic Programming, 10th International Conference, 2000


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