Jan Ramon - RankMe

126 papers A* 10A 2B 17C 3Misc 2Journal 57Unranked 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Accurate, private, secure, federated U-statistics with higher degree. CoRR Quentin Sinh, Jan Ramon
2026	J	`jnl`	DDH-based schemes for multi-party Function Secret Sharing. CoRR Marc Damie, Florian Hahn, Andreas Peter, Jan Ramon
2025	J	`jnl`	A Survey on Verifiable Cross-Silo Federated Learning. Trans. Mach. Learn. Res. Aleksei Korneev, Jan Ramon
2025	—	`conf`	DDH-Based Schemes for Multi-party Function Secret Sharing. NordSec Marc Damie, Florian Hahn, Andreas Peter, Jan Ramon
2025	J	`jnl`	DDH-based schemes for multi-party Function Secret Sharing. IACR Cryptol. ePrint Arch. Marc Damie, Florian Hahn, Andreas Peter, Jan Ramon
2025	J	`jnl`	Differentially Private Empirical Cumulative Distribution Functions. CoRR Antoine Barczewski, Amal Mawass, Jan Ramon
2025	J	`jnl`	Dropout-Robust Mechanisms for Differentially Private and Fully Decentralized Mean Estimation. CoRR César Sabater, Sonia Ben Mokhtar, Jan Ramon
2025	J	`jnl`	Eliminating Exponential Key Growth in PRG-Based Distributed Point Functions. CoRR Marc Damie, Florian Hahn, Andreas Peter, Jan Ramon
2025	J	`jnl`	Eliminating Exponential Key Growth in PRG-Based Distributed Point Functions. IACR Cryptol. ePrint Arch. Marc Damie, Florian Hahn, Andreas Peter, Jan Ramon
2025	J	`jnl`	Gradient Projection onto Historical Descent Directions for Communication-Efficient Federated Learning. CoRR Arnaud Descours, Léonard Deroose, Jan Ramon
2025	J	`jnl`	How to Securely Shuffle? A survey about Secure Shufflers for privacy-preserving computations. CoRR Marc Damie, Florian Hahn, Andreas Peter, Jan Ramon
2025	J	`jnl`	Noisy Function Secret Sharing and its applications to Differentially Private computations. IACR Cryptol. ePrint Arch. Marc Damie, Federico Mazzone, Florian Hahn, Andreas Peter, Jan Ramon
2025	J	`jnl`	Secure Sparse Matrix Multiplications and their Applications to Privacy-Preserving Machine Learning. CoRR Marc Damie, Florian Hahn, Andreas Peter, Jan Ramon
2024	C	`conf`	Honest Fraction Differential Privacy. IH&MMSec Imane Taibi, Jan Ramon
2024	J	`jnl`	Linear Programs with Conjunctive Database Queries. Log. Methods Comput. Sci. Florent Capelli, Nicolas Crosetti, Joachim Niehren, Jan Ramon
2024	J	`jnl`	SoK: Verifiable Cross-Silo FL. CoRR Aleksei Korneev, Jan Ramon
2023	J	`jnl`	DP-SGD with weight clipping. CoRR Antoine Barczewski, Jan Ramon
2023	Misc	`conf`	Introducing the TRUMPET project: TRUstworthy Multi-site Privacy Enhancing Technologies. CSR 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 Luaña, Gonzalo Jiménez-Balsa
2023	J	`jnl`	Limits of multi-relational graphs. Mach. Learn. Juan Alvarado, Yuyi Wang, Jan Ramon
2023	J	`jnl`	Private Sampling with Identifiable Cheaters. Proc. Priv. Enhancing Technol. César Sabater, Florian Hahn, Andreas Peter, Jan Ramon
2022	J	`jnl`	An accurate, scalable and verifiable protocol for federated differentially private averaging. Mach. Learn. César Sabater, Aurélien Bellet, Jan Ramon
2022	J	`jnl`	Linear Programs with Conjunctive Database Queries. CoRR Florent Capelli, Nicolas Crosetti, Joachim Niehren, Jan Ramon
2022	A	`conf`	Linear Programs with Conjunctive Queries. ICDT Florent Capelli, Nicolas Crosetti, Joachim Niehren, Jan Ramon
2020	J	`jnl`	Distributed Differentially Private Averaging with Improved Utility and Robustness to Malicious Parties. CoRR César Sabater, Aurélien Bellet, Jan Ramon
2020	—	`conf`	Interpretable Privacy with Optimizable Utility. PKDD/ECML Workshops Jan Ramon, Moitree Basu
2019	J	`jnl`	Dependency Weighted Aggregation on Factorized Databases. CoRR Florent Capelli, Nicolas Crosetti, Joachim Niehren, Jan Ramon
2018	J	`jnl`	A machine learning based framework to identify and classify long terminal repeat retrotransposons. PLoS Comput. Biol. Leander Schietgat, Celine Vens, Ricardo Cerri, Carlos N. Fischer, Eduardo P. Costa, Jan Ramon, Claudia M. A. Carareto, Hendrik Blockeel
2018	J	`jnl`	Graph sampling with applications to estimating the number of pattern embeddings and the parameters of a statistical relational model. Data Min. Knowl. Discov. Irma Ravkic, Martin Znidarsic, Jan Ramon, Jesse Davis
2018	J	`jnl`	Hiding in the Crowd: A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries. CoRR Pierre Dellenbach, Aurélien Bellet, Jan Ramon
2017	B	`conf`	Learning from Networked Examples. ALT Yuyi Wang, Zheng-Chu Guo, Jan Ramon
2016	A*	`conf`	Bounds for Learning from Evolutionary-Related Data in the Realizable Case. IJCAI Ondrej Kuzelka, Yuyi Wang, Jan Ramon
2016	J	`jnl`	Guest editors introduction: special issue on inductive logic programming. Mach. Learn. Jesse Davis, Jan Ramon
2015	—	`conf`	A Note on Restricted Forms of LGG. ILP (Late Breaking Papers) Ondrej Kuzelka, Jan Ramon
2015	B	`ed.`	Inductive Logic Programming - 24th International Conference, ILP 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers ILP Jesse Davis, Jan Ramon
2015	J	`jnl`	Learning relational dependency networks in hybrid domains. Mach. Learn. Irma Ravkic, Jan Ramon, Jesse Davis
2015	B	`conf`	Mine 'Em All: A Note on Mining All Graphs. ILP Ondrej Kuzelka, Jan Ramon
2015	J	`jnl`	Naive Infinite Enumeration of Context-free Languages in Incremental Polynomial Time. J. Univers. Comput. Sci. Christophe Costa Florêncio, Jonny Daenen, Jan Ramon, Jan Van den Bussche, Dries Van Dyck
2015	J	`jnl`	Predicate logic as a modeling language: modeling and solving some machine learning and data mining problems with Theory Pract. Log. Program. Maurice Bruynooghe, Hendrik Blockeel, Bart Bogaerts, Broes De Cat, Stef De Pooter, Joachim Jansen, Anthony Labarre, Jan Ramon, Marc Denecker, Sicco Verwer
2015	B	`conf`	Predicting Protein Function and Protein-Ligand Interaction with the 3D Neighborhood Kernel. Discovery Science Leander Schietgat, Thomas Fannes, Jan Ramon
2014	—	`ch.`	Graph and Network Pattern Mining. Mining User Generated Content Jan Ramon, Constantin Comendant, Mostafa Haghir Chehreghani, Yuyi Wang
2014	J	`jnl`	Learning from networked examples. CoRR Yuyi Wang, Jan Ramon, Zheng-Chu Guo
2014	Misc	`conf`	Towards a Framework for Learning from Networked Data. ICCS Jan Ramon
2014	—	`conf`	U-statistics on network-structured data with kernels of degree larger than one. SSDM@ECML/PKDD Yuyi Wang, Christos Pelekis, Jan Ramon
2013	J	`jnl`	A polynomial-time maximum common subgraph algorithm for outerplanar graphs and its application to chemoinformatics. Ann. Math. Artif. Intell. Leander Schietgat, Jan Ramon, Maurice Bruynooghe
2013	J	`jnl`	An efficiently computable subgraph pattern support measure: counting independent observations. Data Min. Knowl. Discov. Yuyi Wang, Jan Ramon, Thomas Fannes
2013	—	`conf`	Detecting Bicliques in GF[q]. ECML/PKDD (1) Jan Ramon, Pauli Miettinen, Jilles Vreeken
2013	—	`conf`	Efficient Frequent Connected Induced Subgraph Mining in Graphs of Bounded Tree-Width. ECML/PKDD (1) Tamás Horváth, Keisuke Otaki, Jan Ramon
2013	C	`conf`	Guided Monte Carlo Tree Search for Planning in Learned Environments. ACML Jelle Van Eyck, Jan Ramon, Fabian Güiza Grandas, Geert Meyfroidt, Maurice Bruynooghe, Greta Van den Berghe
2013	J	`jnl`	Learning from networked examples in a k-partite graph. CoRR Yuyi Wang, Jan Ramon, Zheng-Chu Guo
2013	J	`jnl`	Nearly exact mining of frequent trees in large networks. Data Min. Knowl. Discov. Ashraf M. Kibriya, Jan Ramon
2013	J	`jnl`	PIUS: peptide identification by unbiased search. Bioinform. Eduardo P. Costa, Gerben Menschaert, Walter Luyten, Kurt De Grave, Jan Ramon
2013	J	`jnl`	Predicate Logic as a Modeling Language: Modeling and Solving some Machine Learning and Data Mining Problems with IDP3. CoRR Maurice Bruynooghe, Hendrik Blockeel, Bart Bogaerts, Broes De Cat, Stef De Pooter, Joachim Jansen, Anthony Labarre, Jan Ramon, Marc Denecker, Sicco Verwer
2012	—	`conf`	An Efficiently Computable Support Measure for Frequent Subgraph Pattern Mining. ECML/PKDD (1) Yuyi Wang, Jan Ramon
2012	—	`conf`	Hybrid Logical Bayesian Networks. ILP (Late Breaking Papers) Irma Ravkic, Jan Ramon, Jesse Davis
2012	—	`conf`	Modeling Machine Learning and Data Mining Problems with FO(·). ICLP (Technical Communications) Hendrik Blockeel, Bart Bogaerts, Maurice Bruynooghe, Broes De Cat, Stef De Pooter, Marc Denecker, Anthony Labarre, Jan Ramon, Sicco Verwer
2012	—	`conf`	Nearly Exact Mining of Frequent Trees in Large Networks. ECML/PKDD (1) Ashraf M. Kibriya, Jan Ramon
2012	A*	`conf`	Open Problem: Learning Dynamic Network Models from a Static Snapshot. COLT Jan Ramon, Constantin Comendant
2011	J	`jnl`	All normalized anti-monotonic overlap graph measures are bounded. Data Min. Knowl. Discov. Toon Calders, Jan Ramon, Dries Van Dyck
2011	J	`jnl`	Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model. BMC Medical Informatics Decis. Mak. 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
2011	J	`jnl`	Effective feature construction by maximum common subgraph sampling. Mach. Learn. Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt
2011	J	`jnl`	Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs CoRR Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele
2011	J	`jnl`	Preface. Fundam. Informaticae Jan Ramon, Fabrizio Costa, Christophe Costa Florêncio, Joost N. Kok
2010	J	`jnl`	A comparison of pruning criteria for probability trees. Mach. Learn. Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe
2010	—	`conf`	Efficient frequent connected subgraph mining in graphs of bounded tree-width. LWA Tamás Horváth, Jan Ramon
2010	J	`jnl`	Efficient frequent connected subgraph mining in graphs of bounded tree-width. Theor. Comput. Sci. Tamás Horváth, Jan Ramon
2010	J	`jnl`	Frequent subgraph mining in outerplanar graphs. Data Min. Knowl. Discov. Tamás Horváth, Jan Ramon, Stefan Wrobel
2010	—	`ch.`	Inductive Queries for a Drug Designing Robot Scientist. Inductive Databases and Constraint-Based Data Mining Ross D. King, Amanda C. Schierz, Amanda Clare, Jem J. Rowland, Andrew Sparkes, Siegfried Nijssen, Jan Ramon
2010	—	`ch.`	Learning with Whom to Communicate Using Relational Reinforcement Learning. Interactive Collaborative Information Systems Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens, H. Jaap van den Herik, Eric O. Postma
2010	J	`jnl`	Prediction of Clinical Conditions after Coronary Bypass Surgery using Dynamic Data Analysis. J. Medical Syst. Kristien Van Loon, Fabian Güiza Grandas, Geert Meyfroidt, Jean-Marie Aerts, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe, Daniel Berckmans
2009	J	`jnl`	An evolutionary game-theoretic analysis of poker strategies. Entertain. Comput. Marc J. V. Ponsen, Karl Tuyls, Michael Kaisers, Jan Ramon
2009	—	`conf`	Context-free Graph Grammars as a Language-bias Mechanism for Graph Pattern Mining. MLG/SRL@ILP Christophe Costa Florêncio, Jan Ramon, Jonny Daenen, Jan Van den Bussche, Dries Van Dyck
2009	J	`jnl`	Deriving distance metrics from generality relations. Pattern Recognit. Lett. Luc De Raedt, Jan Ramon
2009	—	`conf`	Dynamic Data Analysis and Data Mining for Prediction of Clinical Stability. MIE Kristien Van Loon, Fabian Güiza Grandas, Geert Meyfroidt, Jean-Marie Aerts, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe, Daniel Berckmans
2009	—	`conf`	Handling missing values and censored data in PCA of pharmacological matrices. KDD Workshop on Statistical and Relational Learning in Bioinformatics Jan Ramon, Fabrizio Costa
2009	—	`conf`	Learning with whom to communicate using relational reinforcement learning. AAMAS (2) Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens
2009	—	`conf`	Maximum Common Subgraph Mining: A Fast and Effective Approach towards Feature Generation. MLG/SRL@ILP Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt
2009	C	`conf`	Monte-Carlo Tree Search in Poker Using Expected Reward Distributions. ACML Guy Van den Broeck, Kurt Driessens, Jan Ramon
2009	J	`jnl`	Polynomial-Delay Enumeration of Monotonic Graph Classes. J. Mach. Learn. Res. Jan Ramon, Siegfried Nijssen
2009	—	`ed.`	Proceedings of the ACM SIGKDD Workshop on Statistical and Relational Learning in Bioinformatics, Paris, France, June 28, 2009 KDD Workshop on Statistical and Relational Learning in Bioinformatics Christophe Costa Florêncio, Fabrizio Costa, Jan Ramon, Joost N. Kok
2009	J	`jnl`	StReBio'09: statistical relational learning and mining in bioinformatics. SIGKDD Explor. Jan Ramon, Fabrizio Costa, Christophe Costa Florêncio, Joost N. Kok
2008	B	`conf`	Active Learning for High Throughput Screening. Discovery Science Kurt De Grave, Jan Ramon, Luc De Raedt
2008	B	`conf`	An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules. Discovery Science Leander Schietgat, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel
2008	A*	`conf`	Anti-monotonic Overlap-Graph Support Measures. ICDM Toon Calders, Jan Ramon, Dries Van Dyck
2008	A*	`conf`	Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker. AAAI Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, Kurt Driessens, Karl Tuyls
2008	—	`conf`	Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth. ECML/PKDD (1) Tamás Horváth, Jan Ramon
2008	J	`jnl`	Generalized ordering-search for learning directed probabilistic logical models. Mach. Learn. Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe
2008	B	`ed.`	Inductive Logic Programming, 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers ILP Hendrik Blockeel, Jan Ramon, Jude W. Shavlik, Prasad Tadepalli
2008	J	`jnl`	Learning directed probabilistic logical models: ordering-search versus structure-search. Ann. Math. Artif. Intell. Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel
2008	—	`conf`	Min, Max and PTIME Anti-Monotonic Overlap Graph Measures. MLG@ICML Toon Calders, Jan Ramon, Dries Van Dyck
2008	A	`conf`	Using Decision Trees as the Answer Networks in Temporal Difference-Networks. ECAI Laura-Andreea Antanas, Kurt Driessens, Jan Ramon, Tom Croonenborghs
2007	—	`conf`	A Polynomial-time Metric for Outerplanar Graphs. MLG Leander Schietgat, Jan Ramon, Maurice Bruynooghe
2007	—	`conf`	General Graph Refinement with Polynomial Delay. MLG Jan Ramon, Siegfried Nijssen
2007	B	`conf`	Learning Directed Probabilistic Logical Models Using Ordering-Search. ILP Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel
2007	—	`conf`	Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search. ECML Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel
2007	J	`jnl`	Mining data from intensive care patients. Adv. Eng. Informatics Jan Ramon, Daan Fierens, Fabian Güiza Grandas, Geert Meyfroidt, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe
2007	A*	`conf`	On Policy Learning in Restricted Policy Spaces. AAAI Robby Goetschalckx, Jan Ramon
2007	A*	`conf`	Online Learning and Exploiting Relational Models in Reinforcement Learning. IJCAI Tom Croonenborghs, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe
2007	—	`conf`	Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling. ECML Jan Ramon, Kurt Driessens, Tom Croonenborghs
2006	—	`conf`	Frequent Subgraph Mining in Outerplanar Graphs. LWA Tamás Horváth, Jan Ramon, Stefan Wrobel
2006	A*	`conf`	Frequent subgraph mining in outerplanar graphs. KDD Tamás Horváth, Jan Ramon, Stefan Wrobel
2006	B	`conf`	Generalized Ordering-Search for Learning Directed Probabilistic Logical Models. ILP Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe
2006	J	`jnl`	Graph kernels and Gaussian processes for relational reinforcement learning. Mach. Learn. Kurt Driessens, Jan Ramon, Thomas Gärtner
2006	B	`conf`	ReMauve: A Relational Model Tree Learner. ILP Celine Vens, Jan Ramon, Hendrik Blockeel
2006	—	`conf`	Refining Aggregate Conditions in Relational Learning. PKDD Celine Vens, Jan Ramon, Hendrik Blockeel
2005	—	`conf`	A Comparison of Approaches for Learning Probability Trees. ECML Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe
2005	—	`conf`	Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. BNAIC Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon
2005	B	`conf`	Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. ILP Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon
2005	—	`conf`	Multi-agent Relational Reinforcement Learning. LAMAS Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice Bruynooghe
2004	J	`jnl`	Compact Representation of Knowledge Bases in Inductive Logic Programming. Mach. Learn. Jan Struyf, Jan Ramon, Maurice Bruynooghe, Sofie Verbaeten, Hendrik Blockeel
2004	A*	`conf`	Condensed Representations for Inductive Logic Programming. KR Luc De Raedt, Jan Ramon
2004	—	`conf`	Searching for Compound Goals Using Relevancy Zones in the Game of Go. Computers and Games Jan Ramon, Tom Croonenborghs
2003	B	`conf`	Graph Kernels and Gaussian Processes for Relational Reinforcement Learning. ILP Thomas Gärtner, Kurt Driessens, Jan Ramon
2003	A*	`conf`	Relational Instance Based Regression for Relational Reinforcement Learning. ICML Kurt Driessens, Jan Ramon
2002	J	`jnl`	Clustering and instance based learning in first order logic. AI Commun. Jan Ramon
2002	B	`conf`	Compact Representation of Knowledge Bases in ILP. ILP Jan Struyf, Jan Ramon, Hendrik Blockeel
2002	J	`jnl`	Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs. J. Artif. Intell. Res. Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele
2001	J	`jnl`	A polynomial time computable metric between point sets. Acta Informatica Jan Ramon, Maurice Bruynooghe
2001	—	`conf`	Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner. ECML Kurt Driessens, Jan Ramon, Hendrik Blockeel
2000	B	`conf`	Executing Query Packs in ILP. ILP Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele
2000	—	`conf`	Learning a Go Heuristic with TILDE. Computers and Games Jan Ramon, Tom Francis, Hendrik Blockeel
2000	J	`jnl`	Top-down induction of clustering trees CoRR Hendrik Blockeel, Luc De Raedt, Jan Ramon
2000	—	`conf`	Using Belief Networks to Neutralize Known Dependencies in Conceptual Clustering. ILP Work-in-progress reports Jan Ramon, Luc Dehaspe
1999	B	`conf`	Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms. ILP Shan-Hwei Nienhuys-Cheng, Wim Van Laer, Jan Ramon, Luc De Raedt
1999	B	`conf`	Instance Based Function Learning. ILP Jan Ramon, Luc De Raedt
1998	B	`conf`	A Framework for Defining Distances Between First-Order Logic Objects. ILP Jan Ramon, Maurice Bruynooghe
1998	A*	`conf`	Top-Down Induction of Clustering Trees. ICML Hendrik Blockeel, Luc De Raedt, Jan Ramon