S. Verwer

发表

Auction optimization with models learned from data

Q. C. Ye, S. Verwer, Yingqian Zhang, 2014 .

BSR winter school Big Software on the Run : Where Software meets Data

Wil M.P. van der Aalst, Boudewijn F. van Dongen, J. V. van Wijk, 2016 .

Polynomial Distinguishability of Timed Automata 1

C. Witteveen, S. Verwer, 2012 .

PAutomaC : a PFA / HMM Learning Competition

C. D. L. Higuera, Rémi Eyraud, S. Verwer, 2012 .

Delft University of Technology An Experience Report on Applying Passive Learning in a Large-Scale Payment

A. Deursen, M. Aniche, S. Verwer, 2017 .

A likelihood-ratio test for identifying probabilistic deterministic real-time automata from positive data (extended abstract)

Cees Witteveen, M. M. De Weerdt, Sicco Verwer, 2010 .

SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting

S. Verwer, A. Nadeem, 2022, 2206.12190.

Enabling Visual Analytics via Alert-driven Attack Graphs

Sicco Verwer, Shanchieh Jay Yang, Stephen Moskal, 2021, CCS.

Robust Optimal Classification Trees Against Adversarial Examples pdf

Sicco Verwer, Daniel Vos, S. Verwer, 2021, AAAI.

Proceedings of Machine Learning Research: International Conference on Grammatical Inference

Menno van Zaanen, Sicco Verwer, Rick Smetsers, 2016 .

Learning fuzzy decision trees using integer optimization

Uzay Kaymak, Sicco Verwer, Alp Akcay, 2018 .

Data driven design for online industrial auctions

Yingqian Zhang, Sicco Verwer, Qing Chuan Ye, 2021, Annals of Mathematics and Artificial Intelligence.

Integrating Testing And Learning of Interface Automata (ITALIA)

Frits W. Vaandrager, Sicco Verwer, Fides Aarts, 2012 .

Hybrid Connection and Host Clustering for Community Detection in Spatial-Temporal Network Data

Sicco Verwer, Azqa Nadeem, M. P. Roeling, 2020, PKDD/ECML Workshops.

Proceedings of the 13th International Conference on Grammatical Inference, ICGI 2016, Delft, The Netherlands, October 5-7, 2016

Sicco Verwer, M. van Zaanen, Rick Smetsers, 2017, ICGI.

Probabilistic Protocol Analysis of Care Processes

Peter J. F. Lucas, Sicco Verwer, Arjen Hommersom, 2013 .

Efficient Identification of Timed Automata

Cees Witteveen, M. M. De Weerdt, Sicco Verwer, 2005 .

Timed Inference for Behavioral Pattern Recognition

Cees Witteveen, Mathijs de Weerdt, Sicco Verwer, 2005, Belgium-Netherlands Conference on Artificial Intelligence.

Learning state machines via efficient hashing of future traces

Robert Baumgartner, S. Verwer, 2022, ArXiv.

Robust Attack Graph Generation

S. Verwer, D. Mouwen, A. Nadeem, 2022, ArXiv.

The First AI4TSP Competition

Reza Refaei Afshar, M. López-Ibáñez, Meinolf Sellmann, 2022 .

EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions

R. Karlsson, S. Verwer, L. Bliek, 2021, ArXiv.

Software model synthesis using satisfiability solvers

Marijn J. H. Heule, S. Verwer, 2013, Empirical Software Engineering.

PAutomaC: a probabilistic automata and hidden Markov models learning competition

C. D. L. Higuera, Rémi Eyraud, S. Verwer, 2014, Machine Learning.

Accelerating Cluster Assignment for SeqClu

S. Verwer, Rami Al-obaidi, 2021 .

Beyond Labeling: Using Clustering to Build Network Behavioral Profiles of Malware Families

Sicco Verwer, Christian Hammerschmidt, Azqa Nadeem, 2020, Malware Analysis Using Artificial Intelligence and Deep Learning.

Beyond Labeling: Intuitive Capability Assessment of Malware using Network Behavioral Profiles

Sicco Verwer, Christian Hammerschmidt, Carlos Gañán, 2019 .

MalPaCA: Malware Packet Sequence Clustering and Analysis pdf

Sicco Verwer, Carlos Hernandez Gañán, Azqa Nadeem, 2019, ArXiv.

Sharing confidential data for algorithm development by multiple imputation

Sicco Verwer, Susan W. van den Braak, Sunil Choenni, 2013, SSDBM.

The Robust Malware Detection Challenge and Greedy Random Accelerated Multi-Bit Search

Abdullah Al-Dujaili, Una-May O'Reilly, A. Nadeem, 2020, AISec@CCS.

Exact DFA Identification Using SAT Solvers

Marijn J. H. Heule, Marijn Heule, Sicco Verwer, 2010, ICGI.

Using a satisfiability solver to identify deterministic finite state automata

Marijn J. H. Heule, Sicco Verwer, Marienus Heule, 2009, BNAIC 2009.

Learning Optimal Classification Trees Using a Binary Linear Program Formulation

Yingqian Zhang, Sicco Verwer, S. Verwer, 2019, BNAIC/BENELEARN.

Learning Decision Trees with Flexible Constraints and Objectives Using Integer Optimization

Yingqian Zhang, Sicco Verwer, S. Verwer, 2017, CPAIOR.

Classifying Socially Sensitive Data Without Discrimination: An Analysis of a Crime Suspect Dataset

Sicco Verwer, Asim Karim, Faisal Kamiran, 2012, 2012 IEEE 12th International Conference on Data Mining Workshops.

SoK: Explainable Machine Learning for Computer Security Applications

Robert Baumgartner, S. Verwer, Luca Pajola, 2022, 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P).

Encoding NetFlows for State-Machine Learning

S. Verwer, Agathe Blaise, Filippo Rebecchi, 2022, ArXiv.

Learning State Machines to Monitor and Detect Anomalies on a Kubernetes Cluster

S. Verwer, Agathe Blaise, Filippo Rebecchi, 2022, ARES.

Alert-Driven Attack Graph Generation Using S-PDFA

S. Verwer, A. Nadeem, Stephen Moskal, 2022, IEEE Transactions on Dependable and Secure Computing.

Intelligent Malware Defenses

W. Joosen, S. Verwer, Vera Rimmer, 2022, Security and Artificial Intelligence.

Efficient Training of Robust Decision Trees Against Adversarial Examples pdf

Sicco Verwer, Daniel Vos, S. Verwer, 2020, ICML.

TABOR: A Graphical Model-based Approach for Anomaly Detection in Industrial Control Systems

Qin Lin, Sridhar Adepu, Aditya Mathur, 2018, AsiaCCS.

Additional Reviewers

Aleksandra Tesanovic, Sicco Verwer, Evgeny Knutov, 2003, PDP.

Three naive Bayes approaches for discrimination-free classification

Toon Calders, Sicco Verwer, T. Calders, 2010, Data Mining and Knowledge Discovery.

Black-box mixed-variable optimisation using a surrogate model that satisfies integer constraints

Mathijs de Weerdt, Sicco Verwer, Laurens Bliek, 2020, GECCO Companion.

Lane-Change Intention Estimation for Car-Following Control in Autonomous Driving

Qin Lin, Jun Wang, Sicco Verwer, 2018, IEEE Transactions on Intelligent Vehicles.

MOHA: A Multi-Mode Hybrid Automaton Model for Learning Car-Following Behaviors

Jun Wang, Sicco Verwer, Yihuan Zhang, 2019, IEEE Transactions on Intelligent Transportation Systems.

Modeling and analysis of non-homogenous fabrication/assembly systems with multiple failure modes

Tian Xia, Junqiang Wang, Sicco Verwer, 2018 .

Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case

Peter J. F. Lucas, Sicco Verwer, Arjen Hommersom, 2016, PGM 2016.

Discovering Probabilistic Structures of Healthcare Processes

Peter J. F. Lucas, Sicco Verwer, Arjen Hommersom, 2013, KR4HC/ProHealth.

Reliable Machine Learning for Networking: Key Issues and Approaches

Radu State, Sicco Verwer, Sebastian Garcia, 2017, 2017 IEEE 42nd Conference on Local Computer Networks (LCN).

Learning Driving Behavior by Timed Syntactic Pattern Recognition

Cees Witteveen, Mathijs de Weerdt, Sicco Verwer, 2011, IJCAI.

Mechanism for Robust Procurements

Yingqian Zhang, Sicco Verwer, S. Verwer, 2012, PRIMA.

Results of the Sequence PredIction ChallengE (SPiCe): a Competition on Learning the Next Symbol in a Sequence

Ariadna Quattoni, Borja Balle, Sicco Verwer, 2016, ICGI.

Behavioral clustering of non-stationary IP flow record data

Radu State, Samuel Marchal, Sicco Verwer, 2016, 2016 12th International Conference on Network and Service Management (CNSM).

Modeling and analysis of non-homogenous fabrication/assembly systems with multiple failure modes

S. Verwer, Jun-qiang Wang, Peng Cui, 2017, The International Journal of Advanced Manufacturing Technology.

Continuous surrogate-based optimization algorithms are well-suited for expensive discrete problems pdf

Mathijs de Weerdt, Sicco Verwer, Rickard Karlsson, 2020, BNAIC/BENELEARN.

Predicate logic as a modeling language: modeling and solving some machine learning and data mining problems with IDP3

Maurice Bruynooghe, Jan Ramon, Hendrik Blockeel, 2013, Theory and Practice of Logic Programming.

Solving bin-packing problems under privacy preservation: Possibilities and trade-offs

Zekeriya Erkin, Sicco Verwer, Yingqian Zhang, 2019, Inf. Sci..

Bigger is Not Always Better: on the Quality of Hypotheses in Active Automata Learning

Frits W. Vaandrager, Sicco Verwer, Rick Smetsers, 2014, ICGI.

Baseband-Function Placement With Multi-Task Traffic Prediction for 5G Radio Access Networks

Tias Guns, S. Verwer, G. Maier, 2022, IEEE Transactions on Network and Service Management.

Differentially-Private Decision Trees with Probabilistic Robustness to Data Poisoning

Z. Erkin, S. Verwer, D. Vos, 2023, arXiv.org.

Combining and Analyzing Judicial Databases

Sicco Verwer, Susan W. van den Braak, Sunil Choenni, 2013, Discrimination and Privacy in the Information Society.

SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting

S. Verwer, A. Nadeem, 2022, ECML/PKDD.

ENCODE: Encoding NetFlows for Network Anomaly Detection

S. Verwer, Agathe Blaise, Filippo Rebecchi, 2022, 2207.03890.

flexfringe: A Passive Automaton Learning Package

Sicco Verwer, Christian A. Hammerschmidt, S. Verwer, 2017, 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME).

Learning behavioral fingerprints from Netflows using Timed Automata

Qin Lin, Sicco Verwer, Gaetano Pellegrino, 2017, 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM).

Auction optimization using regression trees and linear models as integer programs

Yingqian Zhang, Sicco Verwer, Qing Chuan Ye, 2017, Artif. Intell..

Black-box combinatorial optimization using models with integer-valued minima

M. D. Weerdt, S. Verwer, Laurens Bliek, 2019, Annals of Mathematics and Artificial Intelligence.

Merging Partially Labelled Trees: Hardness and a Declarative Programming Solution

Anthony Labarre, Sicco Verwer, S. Verwer, 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

An algorithm for learning real-time automata

Cees Witteveen, Sicco Verwer, M. M. De Weerdt, 2007 .

Optimal Decision Tree Policies for Markov Decision Processes

S. Verwer, D. Vos, 2023, IJCAI.

Efficiently identifying deterministic real-time automata from labeled data

C. Witteveen, M. D. Weerdt, S. Verwer, 2012, Machine Learning.

Learning Deterministic Finite Automata from Infinite Alphabets

Qin Lin, Sicco Verwer, Gaetano Pellegrino, 2016, ICGI.

Improving active Mealy machine learning for protocol conformance testing

Frits W. Vaandrager, Sicco Verwer, Jan Tretmans, 2014, Machine Learning.

Learning state machines from data streams: A generic strategy and an improved heuristic

Robert Baumgartner, S. Verwer, 2023, ICGI.

The efficiency of identifying timed automata and the power of clocks

Cees Witteveen, Mathijs de Weerdt, Sicco Verwer, 2011, Inf. Comput..

One-Clock Deterministic Timed Automata Are Efficiently Identifiable in the Limit

Cees Witteveen, Mathijs de Weerdt, Sicco Verwer, 2009, LATA.

Polynomial Distinguishability of Timed Automata

Cees Witteveen, Mathijs de Weerdt, Sicco Verwer, 2008, ICGI.

Regular inference as vertex coloring

Sicco Verwer, Christophe Costa Florêncio, C. C. Florêncio, 2012, Theor. Comput. Sci..

Anomaly Detection in a Digital Video Broadcasting System Using Timed Automata pdf

Qin Lin, Sicco Verwer, Xiaoran Liu, 2017, ArXiv.

Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case

Marcos L. P. Bueno, Peter J.F. Lucas, S. Verwer, 2016, Probabilistic Graphical Models.

Estimating Prediction Certainty in Decision Trees

Hendrik Blockeel, Sicco Verwer, Eduardo P. Costa, 2013, IDA.

Additional Reviewers

A. Tesanovic, E. Knutov, S. Verwer, 2010 .

Complementing Model Learning with Mutation-Based Fuzzing pdf

Sicco Verwer, Rick Smetsers, Joshua Moerman, 2016, ArXiv.

FlexFringe: Modeling Software Behavior by Learning Probabilistic Automata

Christian A. Hammerschmidt, S. Verwer, 2022, ArXiv.

Software model synthesis using satisfiability solvers

Marijn J. H. Heule, Marijn Heule, Sicco Verwer, 2012, Empirical Software Engineering.

CATMA: Conformance Analysis Tool For Microservice Applications

S. Verwer, Annibale Panichella, Clinton Cao, 2024, ArXiv.

Safety Verification of a Data-driven Adaptive Cruise Controller

Sicco Verwer, John Dolan, Qin Lin, 2020, 2020 IEEE Intelligent Vehicles Symposium (IV).

Learning a Safety Verifiable Adaptive Cruise Controller from Human Driving Data pdf

Sicco Verwer, Qin Lin, John Dolan, 2019, ArXiv.