Jan Ramon

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 18

Top Venues

CoRR

Mach. Learn.

Discovery Science

ILP (Late Breaking Papers)

Publications

Florent Capelli, Nicolas Crosetti, Joachim Niehren, Jan Ramon
Linear Programs with Conjunctive Database Queries. Log. Methods Comput. Sci. 20 (1) (2024)
Imane Taibi, Jan Ramon
Honest Fraction Differential Privacy. IH&MMSec (2024)
Antoine Barczewski, Jan Ramon
DP-SGD with weight clipping. CoRR (2023)
César Sabater, Florian Hahn, Andreas Peter, Jan Ramon
Private Sampling with Identifiable Cheaters. Proc. Priv. Enhancing Technol. 2023 (2) (2023)
Alberto Pedrouzo-Ulloa, Jan Ramon, Fernando Pérez-González, Siyanna Lilova, Patrick Duflot, Zakaria Chihani, Nicola Gentili, Paola Ulivi, Mohammad Ashadul Hoque, Twaha Mukammel, Zeev Pritzker, Augustin Lemesle, Jaime Loureiro-Acuña, Xavier Martínez, Gonzalo Jiménez-Balsa
Introducing the TRUMPET project: TRUstworthy Multi-site Privacy Enhancing Technologies. CSR (2023)
Juan Alvarado, Yuyi Wang, Jan Ramon
Limits of multi-relational graphs. Mach. Learn. 112 (1) (2023)
Florent Capelli, Nicolas Crosetti, Joachim Niehren, Jan Ramon
Linear Programs with Conjunctive Queries. ICDT (2022)
César Sabater, Aurélien Bellet, Jan Ramon
An accurate, scalable and verifiable protocol for federated differentially private averaging. Mach. Learn. 111 (11) (2022)
Florent Capelli, Nicolas Crosetti, Joachim Niehren, Jan Ramon
Linear Programs with Conjunctive Database Queries. CoRR (2022)
César Sabater, Aurélien Bellet, Jan Ramon
Distributed Differentially Private Averaging with Improved Utility and Robustness to Malicious Parties. CoRR (2020)
Jan Ramon, Moitree Basu
Interpretable Privacy with Optimizable Utility. PKDD/ECML Workshops (2020)
Florent Capelli, Nicolas Crosetti, Joachim Niehren, Jan Ramon
Dependency Weighted Aggregation on Factorized Databases. CoRR (2019)
Leander Schietgat, Celine Vens, Ricardo Cerri, Carlos N. Fischer, Eduardo P. Costa, Jan Ramon, Claudia M. A. Carareto, Hendrik Blockeel
A machine learning based framework to identify and classify long terminal repeat retrotransposons. PLoS Comput. Biol. 14 (4) (2018)
Pierre Dellenbach, Aurélien Bellet, Jan Ramon
Hiding in the Crowd: A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries. CoRR (2018)
Irma Ravkic, Martin Znidarsic, Jan Ramon, Jesse Davis
Graph sampling with applications to estimating the number of pattern embeddings and the parameters of a statistical relational model. Data Min. Knowl. Discov. 32 (4) (2018)
Yuyi Wang, Zheng-Chu Guo, Jan Ramon
Learning from Networked Examples. ALT (2017)
Jesse Davis, Jan Ramon
Guest editors introduction: special issue on inductive logic programming. Mach. Learn. 103 (3) (2016)
Ondrej Kuzelka, Yuyi Wang, Jan Ramon
Bounds for Learning from Evolutionary-Related Data in the Realizable Case. IJCAI (2016)
Maurice Bruynooghe, Hendrik Blockeel, Bart Bogaerts, Broes De Cat, Stef De Pooter, Joachim Jansen, Anthony Labarre, Jan Ramon, Marc Denecker, Sicco Verwer
. Theory Pract. Log. Program. 15 (6) (2015)
Irma Ravkic, Jan Ramon, Jesse Davis
Learning relational dependency networks in hybrid domains. Mach. Learn. 100 (2-3) (2015)
Ondrej Kuzelka, Jan Ramon
A Note on Restricted Forms of LGG. ILP (Late Breaking Papers) (2015)
Christophe Costa Florêncio, Jonny Daenen, Jan Ramon, Jan Van den Bussche, Dries Van Dyck
Naive Infinite Enumeration of Context-free Languages in Incremental Polynomial Time. J. Univers. Comput. Sci. 21 (7) (2015)
Ondrej Kuzelka, Jan Ramon
Mine 'Em All: A Note on Mining All Graphs. ILP (2015)
Leander Schietgat, Thomas Fannes, Jan Ramon
Predicting Protein Function and Protein-Ligand Interaction with the 3D Neighborhood Kernel. Discovery Science (2015)
Yuyi Wang, Christos Pelekis, Jan Ramon
U-statistics on network-structured data with kernels of degree larger than one. SSDM@ECML/PKDD (2014)
Jan Ramon
Towards a Framework for Learning from Networked Data. ICCS (2014)
Yuyi Wang, Jan Ramon, Zheng-Chu Guo
Learning from networked examples. CoRR (2014)
Yuyi Wang, Jan Ramon, Zheng-Chu Guo
Learning from networked examples in a k-partite graph. CoRR (2013)
Jelle Van Eyck, Jan Ramon, Fabian Güiza Grandas, Geert Meyfroidt, Maurice Bruynooghe, Greta Van den Berghe
Guided Monte Carlo Tree Search for Planning in Learned Environments. ACML (2013)
Tamás Horváth, Keisuke Otaki, Jan Ramon
Efficient Frequent Connected Induced Subgraph Mining in Graphs of Bounded Tree-Width. ECML/PKDD (1) (2013)
Maurice Bruynooghe, Hendrik Blockeel, Bart Bogaerts, Broes De Cat, Stef De Pooter, Joachim Jansen, Anthony Labarre, Jan Ramon, Marc Denecker, Sicco Verwer
Predicate Logic as a Modeling Language: Modeling and Solving some Machine Learning and Data Mining Problems with IDP3. CoRR (2013)
Ashraf M. Kibriya, Jan Ramon
Nearly exact mining of frequent trees in large networks. Data Min. Knowl. Discov. 27 (3) (2013)
Jan Ramon, Pauli Miettinen, Jilles Vreeken
Detecting Bicliques in GF[q]. ECML/PKDD (1) (2013)
Yuyi Wang, Jan Ramon, Thomas Fannes
An efficiently computable subgraph pattern support measure: counting independent observations. Data Min. Knowl. Discov. 27 (3) (2013)
Leander Schietgat, Jan Ramon, Maurice Bruynooghe
A polynomial-time maximum common subgraph algorithm for outerplanar graphs and its application to chemoinformatics. Ann. Math. Artif. Intell. 69 (4) (2013)
Eduardo P. Costa, Gerben Menschaert, Walter Luyten, Kurt De Grave, Jan Ramon
PIUS: peptide identification by unbiased search. Bioinform. 29 (15) (2013)
Ashraf M. Kibriya, Jan Ramon
Nearly Exact Mining of Frequent Trees in Large Networks. ECML/PKDD (1) (2012)
Jan Ramon, Constantin Comendant
Open Problem: Learning Dynamic Network Models from a Static Snapshot. COLT (2012)
Hendrik Blockeel, Bart Bogaerts, Maurice Bruynooghe, Broes De Cat, Stef De Pooter, Marc Denecker, Anthony Labarre, Jan Ramon, Sicco Verwer
Modeling Machine Learning and Data Mining Problems with FO(·). ICLP (Technical Communications) (2012)
Irma Ravkic, Jan Ramon, Jesse Davis
Hybrid Logical Bayesian Networks. ILP (Late Breaking Papers) (2012)
Yuyi Wang, Jan Ramon
An Efficiently Computable Support Measure for Frequent Subgraph Pattern Mining. ECML/PKDD (1) (2012)
Toon Calders, Jan Ramon, Dries Van Dyck
All normalized anti-monotonic overlap graph measures are bounded. Data Min. Knowl. Discov. 23 (3) (2011)
Jan Ramon, Fabrizio Costa, Christophe Costa Florêncio, Joost N. Kok
Preface. Fundam. Informaticae 113 (2) (2011)
Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele
Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs CoRR (2011)
Geert Meyfroidt, Fabian Güiza Grandas, Dominiek Cottem, Wilfried De Becker, Kristien Van Loon, Jean-Marie Aerts, Daniel Berckmans, Jan Ramon, Maurice Bruynooghe, Greta Van den Berghe
Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model. BMC Medical Informatics Decis. Mak. 11 (2011)
Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt
Effective feature construction by maximum common subgraph sampling. Mach. Learn. 83 (2) (2011)
Tamás Horváth, Jan Ramon
Efficient frequent connected subgraph mining in graphs of bounded tree-width. Theor. Comput. Sci. 411 (31-33) (2010)
Tamás Horváth, Jan Ramon
Efficient frequent connected subgraph mining in graphs of bounded tree-width. LWA (2010)
Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe
A comparison of pruning criteria for probability trees. Mach. Learn. 78 (1-2) (2010)
Tamás Horváth, Jan Ramon, Stefan Wrobel
Frequent subgraph mining in outerplanar graphs. Data Min. Knowl. Discov. 21 (3) (2010)
Kristien Van Loon, Fabian Güiza Grandas, Geert Meyfroidt, Jean-Marie Aerts, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe, Daniel Berckmans
Prediction of Clinical Conditions after Coronary Bypass Surgery using Dynamic Data Analysis. J. Medical Syst. 34 (3) (2010)
Luc De Raedt, Jan Ramon
Deriving distance metrics from generality relations. Pattern Recognit. Lett. 30 (3) (2009)
Marc J. V. Ponsen, Karl Tuyls, Michael Kaisers, Jan Ramon
An evolutionary game-theoretic analysis of poker strategies. Entertain. Comput. 1 (1) (2009)
Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens
Learning with whom to communicate using relational reinforcement learning. AAMAS (2) (2009)
Kristien Van Loon, Fabian Güiza Grandas, Geert Meyfroidt, Jean-Marie Aerts, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe, Daniel Berckmans
Dynamic Data Analysis and Data Mining for Prediction of Clinical Stability. MIE (2009)
Guy Van den Broeck, Kurt Driessens, Jan Ramon
Monte-Carlo Tree Search in Poker Using Expected Reward Distributions. ACML (2009)
Jan Ramon, Fabrizio Costa, Christophe Costa Florêncio, Joost N. Kok
StReBio'09: statistical relational learning and mining in bioinformatics. SIGKDD Explor. 11 (2) (2009)
Jan Ramon, Siegfried Nijssen
Polynomial-Delay Enumeration of Monotonic Graph Classes. J. Mach. Learn. Res. 10 (2009)
Jan Ramon, Fabrizio Costa
Handling missing values and censored data in PCA of pharmacological matrices. KDD Workshop on Statistical and Relational Learning in Bioinformatics (2009)
Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe
Generalized ordering-search for learning directed probabilistic logical models. Mach. Learn. 70 (2-3) (2008)
Laura-Andreea Antanas, Kurt Driessens, Jan Ramon, Tom Croonenborghs
Using Decision Trees as the Answer Networks in Temporal Difference-Networks. ECAI (2008)
Tamás Horváth, Jan Ramon
Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth. ECML/PKDD (1) (2008)
Toon Calders, Jan Ramon, Dries Van Dyck
Anti-monotonic Overlap-Graph Support Measures. ICDM (2008)
Kurt De Grave, Jan Ramon, Luc De Raedt
Active Learning for High Throughput Screening. Discovery Science (2008)
Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, Kurt Driessens, Karl Tuyls
Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker. AAAI (2008)
Leander Schietgat, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel
An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules. Discovery Science (2008)
Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel
Learning directed probabilistic logical models: ordering-search versus structure-search. Ann. Math. Artif. Intell. 54 (1-3) (2008)
Tom Croonenborghs, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe
Online Learning and Exploiting Relational Models in Reinforcement Learning. IJCAI (2007)
Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel
Learning Directed Probabilistic Logical Models Using Ordering-Search. ILP (2007)
Robby Goetschalckx, Jan Ramon
On Policy Learning in Restricted Policy Spaces. AAAI (2007)
Jan Ramon, Siegfried Nijssen
General Graph Refinement with Polynomial Delay. MLG (2007)
Leander Schietgat, Jan Ramon, Maurice Bruynooghe
A Polynomial-time Metric for Outerplanar Graphs. MLG (2007)
Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel
Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search. ECML (2007)
Jan Ramon, Kurt Driessens, Tom Croonenborghs
Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling. ECML (2007)
Jan Ramon, Daan Fierens, Fabian Güiza Grandas, Geert Meyfroidt, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe
Mining data from intensive care patients. Adv. Eng. Informatics 21 (3) (2007)
Tamás Horváth, Jan Ramon, Stefan Wrobel
Frequent Subgraph Mining in Outerplanar Graphs. LWA (2006)
Kurt Driessens, Jan Ramon, Thomas Gärtner
Graph kernels and Gaussian processes for relational reinforcement learning. Mach. Learn. 64 (1-3) (2006)
Celine Vens, Jan Ramon, Hendrik Blockeel
Refining Aggregate Conditions in Relational Learning. PKDD (2006)
Celine Vens, Jan Ramon, Hendrik Blockeel
ReMauve: A Relational Model Tree Learner. ILP (2006)
Tamás Horváth, Jan Ramon, Stefan Wrobel
Frequent subgraph mining in outerplanar graphs. KDD (2006)
Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe
Generalized Ordering-Search for Learning Directed Probabilistic Logical Models. ILP (2006)
Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon
Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. ILP (2005)
Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon
Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. BNAIC (2005)
Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe
A Comparison of Approaches for Learning Probability Trees. ECML (2005)
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice Bruynooghe
Multi-agent Relational Reinforcement Learning. LAMAS (2005)
Jan Struyf, Jan Ramon, Maurice Bruynooghe, Sofie Verbaeten, Hendrik Blockeel
Compact Representation of Knowledge Bases in Inductive Logic Programming. Mach. Learn. 57 (3) (2004)
Luc De Raedt, Jan Ramon
Condensed Representations for Inductive Logic Programming. KR (2004)
Jan Ramon, Tom Croonenborghs
Searching for Compound Goals Using Relevancy Zones in the Game of Go. Computers and Games (2004)
Kurt Driessens, Jan Ramon
Relational Instance Based Regression for Relational Reinforcement Learning. ICML (2003)
Thomas Gärtner, Kurt Driessens, Jan Ramon
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning. ILP (2003)
Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele
Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs. J. Artif. Intell. Res. 16 (2002)
Jan Struyf, Jan Ramon, Hendrik Blockeel
Compact Representation of Knowledge Bases in ILP. ILP (2002)
Jan Ramon
Clustering and instance based learning in first order logic. AI Commun. 15 (4) (2002)
Jan Ramon, Maurice Bruynooghe
A polynomial time computable metric between point sets. Acta Informatica 37 (10) (2001)
Kurt Driessens, Jan Ramon, Hendrik Blockeel
Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner. ECML (2001)
Jan Ramon, Luc Dehaspe
Using Belief Networks to Neutralize Known Dependencies in Conceptual Clustering. ILP Work-in-progress reports (2000)
Hendrik Blockeel, Luc De Raedt, Jan Ramon
Top-down induction of clustering trees CoRR (2000)
Jan Ramon, Tom Francis, Hendrik Blockeel
Learning a Go Heuristic with TILDE. Computers and Games (2000)
Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele
Executing Query Packs in ILP. ILP (2000)
Jan Ramon, Luc De Raedt
Instance Based Function Learning. ILP (1999)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jan Ramon