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2020 – today
- 2024
[j22]Ligia Maria Moreira Zorello, Laurens Bliek
, Sebastian Troia, Guido Maier, Sicco Verwer:
Black-box optimization for anticipated baseband-function placement in 5G networks. Comput. Networks 245: 110384 (2024)- [c55]Clinton Cao, Simon Schneider, Nicolás E. Díaz Ferreyra, Sicco Verwer, Annibale Panichella, Riccardo Scandariato:
CATMA: Conformance Analysis Tool For Microservice Applications. ICSE Companion 2024: 59-63 - [c54]Robert Baumgartner, Sicco Verwer:
PDFA Distillation with Error Bound Guarantees. CIAA 2024: 51-65 - [c53]Simon Dieck, Sicco Verwer:
On Bidirectional Deterministic Finite Automata. CIAA 2024: 109-123 - [p5]Willem van Jaarsveld, Alp Akçay, Laurens Bliek, Paulo da Costa, Mathijs de Weerdt, Rik Eshuis, Stella Kapodistria, Uzay Kaymak, Verus Pronk, Geert-Jan van Houtum, Peter Verleijsdonk, Sicco Verwer, Simon Voorberg, Yingqian Zhang:
Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration. Commit2Data 2024: 5:1-5:13 - [i31]Clinton Cao, Simon Schneider, Nicolás E. Díaz Ferreyra, Sicco Verwer, Annibale Panichella, Riccardo Scandariato:
CATMA: Conformance Analysis Tool For Microservice Applications. CoRR abs/2401.09838 (2024) - [i30]Hielke Walinga, Robert Baumgartner, Sicco Verwer:
Database-assisted automata learning. CoRR abs/2406.07208 (2024) - [i29]Robert Baumgartner, Sicco Verwer:
PDFA Distillation via String Probability Queries. CoRR abs/2406.18328 (2024) - [i28]Daniël Vos, Sicco Verwer:
Optimizing Interpretable Decision Tree Policies for Reinforcement Learning. CoRR abs/2408.11632 (2024) - [i27]Jacobus G. M. van der Linden, Daniël Vos, Mathijs Michiel de Weerdt, Sicco Verwer, Emir Demirovic:
Optimal or Greedy Decision Trees? Revisiting their Objectives, Tuning, and Performance. CoRR abs/2409.12788 (2024) - 2023
- [j21]Yingqian Zhang, Laurens Bliek, Paulo da Costa, Reza Refaei Afshar, Robbert Reijnen, Tom Catshoek, Daniël Vos, Sicco Verwer, Fynn Schmitt-Ulms, André Hottung, Tapan Shah, Meinolf Sellmann, Kevin Tierney, Carl Perreault-Lafleur, Caroline Leboeuf, Federico Bobbio, Justine Pepin, Warley Almeida Silva, Ricardo Gama, Hugo L. Fernandes, Martin Zaefferer, Manuel López-Ibáñez, Ekhine Irurozki:
The first AI4TSP competition: Learning to solve stochastic routing problems. Artif. Intell. 319: 103918 (2023) - [j20]Laurens Bliek, Arthur Guijt, Rickard Karlsson, Sicco Verwer, Mathijs de Weerdt:
Benchmarking surrogate-based optimisation algorithms on expensive black-box functions. Appl. Soft Comput. 147: 110744 (2023) - [c52]Azqa Nadeem, Daniël Vos, Clinton Cao, Luca Pajola, Simon Dieck, Robert Baumgartner, Sicco Verwer:
SoK: Explainable Machine Learning for Computer Security Applications. EuroS&P 2023: 221-240 - [c51]Simon Dieck, Sicco Verwer:
Learning Syntactic Monoids from Samples by extending known Algorithms for learning State Machines. ICGI 2023: 59-79 - [c50]Robert Baumgartner, Sicco Verwer:
Learning state machines from data streams: A generic strategy and an improved heuristic. ICGI 2023: 117-141 - [c49]Bram Verboom, Simon Dieck, Sicco Verwer:
Detecting Changes in Loop Behavior for Active Learning. ICGI 2023: 142-156 - [c48]Daniël Vos, Sicco Verwer:
Optimal Decision Tree Policies for Markov Decision Processes. IJCAI 2023: 5457-5465 - [i26]Daniël Vos, Sicco Verwer:
Optimal Decision Tree Policies for Markov Decision Processes. CoRR abs/2301.13185 (2023) - [i25]Daniël Vos, Jelle Vos, Tianyu Li, Zekeriya Erkin, Sicco Verwer:
Differentially-Private Decision Trees with Probabilistic Robustness to Data Poisoning. CoRR abs/2305.15394 (2023) - 2022
- [j19]Azqa Nadeem, Sicco Verwer, Stephen Moskal, Shanchieh Jay Yang:
Alert-Driven Attack Graph Generation Using S-PDFA. IEEE Trans. Dependable Secur. Comput. 19(2): 731-746 (2022) - [j18]Ligia Maria Moreira Zorello, Laurens Bliek, Sebastian Troia, Tias Guns, Sicco Verwer, Guido Maier:
Baseband-Function Placement With Multi-Task Traffic Prediction for 5G Radio Access Networks. IEEE Trans. Netw. Serv. Manag. 19(4): 5104-5119 (2022) - [c47]Clinton Cao, Agathe Blaise, Sicco Verwer, Filippo Rebecchi:
Learning State Machines to Monitor and Detect Anomalies on a Kubernetes Cluster. ARES 2022: 117:1-117:9 - [c46]Daniël Vos, Sicco Verwer:
Robust Optimal Classification Trees against Adversarial Examples. AAAI 2022: 8520-8528 - [c45]Azqa Nadeem, Sicco Verwer:
SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting. ECML/PKDD (1) 2022: 157-173 - [c44]Daniël Vos, Sicco Verwer:
Adversarially Robust Decision Tree Relabeling. ECML/PKDD (3) 2022: 203-218 - [p4]Azqa Nadeem, Vera Rimmer, Wouter Joosen, Sicco Verwer:
Intelligent Malware Defenses. Security and Artificial Intelligence 2022: 217-253 - [p3]Vera Rimmer, Azqa Nadeem, Sicco Verwer, Davy Preuveneers, Wouter Joosen:
Open-World Network Intrusion Detection. Security and Artificial Intelligence 2022: 254-283 - [i24]Laurens Bliek, Paulo da Costa, Reza Refaei Afshar, Yingqian Zhang, Tom Catshoek, Daniël Vos, Sicco Verwer, Fynn Schmitt-Ulms, André Hottung, Tapan Shah, Meinolf Sellmann, Kevin Tierney, Carl Perreault-Lafleur, Caroline Leboeuf, Federico Bobbio, Justine Pepin, Warley Almeida Silva, Ricardo Gama, Hugo L. Fernandes, Martin Zaefferer, Manuel López-Ibáñez, Ekhine Irurozki:
The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems. CoRR abs/2201.10453 (2022) - [i23]Sicco Verwer, Christian A. Hammerschmidt:
FlexFringe: Modeling Software Behavior by Learning Probabilistic Automata. CoRR abs/2203.16331 (2022) - [i22]Dennis Mouwen, Sicco Verwer, Azqa Nadeem:
Robust Attack Graph Generation. CoRR abs/2206.07776 (2022) - [i21]Azqa Nadeem, Sicco Verwer:
SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting. CoRR abs/2206.12190 (2022) - [i20]Robert Baumgartner, Sicco Verwer:
Learning state machines via efficient hashing of future traces. CoRR abs/2207.01516 (2022) - [i19]Clinton Cao, Annibale Panichella, Sicco Verwer, Agathe Blaise, Filippo Rebecchi:
Encoding NetFlows for State-Machine Learning. CoRR abs/2207.03890 (2022) - [i18]Clinton Cao, Agathe Blaise, Sicco Verwer, Filippo Rebecchi:
Learning State Machines to Monitor and Detect Anomalies on a Kubernetes Cluster. CoRR abs/2207.12087 (2022) - [i17]Azqa Nadeem, Daniël Vos, Clinton Cao, Luca Pajola, Simon Dieck, Robert Baumgartner, Sicco Verwer:
SoK: Explainable Machine Learning for Computer Security Applications. CoRR abs/2208.10605 (2022) - 2021
- [j17]Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Black-box combinatorial optimization using models with integer-valued minima. Ann. Math. Artif. Intell. 89(7): 639-653 (2021) - [j16]Qing Chuan Ye, Jason Rhuggenaath, Yingqian Zhang, Sicco Verwer, Michiel Jurgen Hilgeman:
Data driven design for online industrial auctions. Ann. Math. Artif. Intell. 89(7): 675-691 (2021) - [c43]Azqa Nadeem, Sicco Verwer, Stephen Moskal, Shanchieh Jay Yang:
Enabling Visual Analytics via Alert-driven Attack Graphs. CCS 2021: 2420-2422 - [c42]Laurens Bliek, Arthur Guijt, Sicco Verwer, Mathijs de Weerdt:
Black-box mixed-variable optimisation using a surrogate model that satisfies integer constraints. GECCO Companion 2021: 1851-1859 - [c41]Daniël Vos, Sicco Verwer:
Efficient Training of Robust Decision Trees Against Adversarial Examples. ICML 2021: 10586-10595 - [c40]Azqa Nadeem, Sicco Verwer, Shanchieh Jay Yang:
SAGE: Intrusion Alert-driven Attack Graph Extractor. VizSec 2021: 36-41 - [i16]Laurens Bliek, Arthur Guijt, Rickard Karlsson, Sicco Verwer, Mathijs de Weerdt:
EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions. CoRR abs/2106.04618 (2021) - [i15]Azqa Nadeem, Sicco Verwer, Stephen Moskal, Shanchieh Jay Yang:
SAGE: Intrusion Alert-driven Attack Graph Extractor. CoRR abs/2107.02783 (2021) - [i14]Daniël Vos, Sicco Verwer:
Robust Optimal Classification Trees Against Adversarial Examples. CoRR abs/2109.03857 (2021) - 2020
- [c39]Rickard Karlsson, Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Continuous Surrogate-Based Optimization Algorithms Are Well-Suited for Expensive Discrete Problems. BNAIC/BENELEARN (Selected Papers) 2020: 48-63 - [c38]Sicco Verwer, Azqa Nadeem, Christian A. Hammerschmidt, Laurens Bliek, Abdullah Al-Dujaili, Una-May O'Reilly:
The Robust Malware Detection Challenge and Greedy Random Accelerated Multi-Bit Search. AISec@CCS 2020: 61-70 - [c37]Qin Lin, Sicco Verwer, John M. Dolan:
Safety Verification of a Data-driven Adaptive Cruise Controller. IV 2020: 2146-2151 - [c36]Mark Patrick Roeling, Azqa Nadeem, Sicco Verwer:
Hybrid Connection and Host Clustering for Community Detection in Spatial-Temporal Network Data. PKDD/ECML Workshops 2020: 178-204 - [i13]Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Black-box Mixed-Variable Optimisation using a Surrogate Model that Satisfies Integer Constraints. CoRR abs/2006.04508 (2020) - [i12]Rickard Karlsson, Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Continuous surrogate-based optimization algorithms are well-suited for expensive discrete problems. CoRR abs/2011.03431 (2020) - [i11]Daniël Vos, Sicco Verwer:
Efficient Training of Robust Decision Trees Against Adversarial Examples. CoRR abs/2012.10438 (2020)
2010 – 2019
- 2019
- [j15]Rowan Hoogervorst, Yingqian Zhang, Gamze Tillem, Zekeriya Erkin, Sicco Verwer:
Solving bin-packing problems under privacy preservation: Possibilities and trade-offs. Inf. Sci. 500: 203-216 (2019) - [j14]Qin Lin, Yihuan Zhang, Sicco Verwer, Jun Wang:
MOHA: A Multi-Mode Hybrid Automaton Model for Learning Car-Following Behaviors. IEEE Trans. Intell. Transp. Syst. 20(2): 790-796 (2019) - [c35]Sicco Verwer, Yingqian Zhang:
Learning Optimal Classification Trees Using a Binary Linear Program Formulation. AAAI 2019: 1625-1632 - [c34]Sicco Verwer, Yingqian Zhang:
Learning Optimal Classification Trees Using a Binary Linear Program Formulation. BNAIC/BENELEARN 2019 - [c33]Qin Lin, Sicco Verwer, Robert E. Kooij, Aditya Mathur:
Using Datasets from Industrial Control Systems for Cyber Security Research and Education. CRITIS 2019: 122-133 - [i10]Azqa Nadeem, Christian A. Hammerschmidt, Carlos Hernandez Gañán, Sicco Verwer:
MalPaCA: Malware Packet Sequence Clustering and Analysis. CoRR abs/1904.01371 (2019) - [i9]Qin Lin, Sicco Verwer, John M. Dolan:
Learning a Safety Verifiable Adaptive Cruise Controller from Human Driving Data. CoRR abs/1910.13526 (2019) - [i8]Laurens Bliek, Sicco Verwer, Mathijs de Weerdt:
Black-box Combinatorial Optimization using Models with Integer-valued Minima. CoRR abs/1911.08817 (2019) - 2018
- [j13]Yihuan Zhang, Qin Lin, Jun Wang, Sicco Verwer, John M. Dolan:
Lane-Change Intention Estimation for Car-Following Control in Autonomous Driving. IEEE Trans. Intell. Veh. 3(3): 276-286 (2018) - [c32]Qin Lin, Sridhar Adepu, Sicco Verwer, Aditya Mathur:
TABOR: A Graphical Model-based Approach for Anomaly Detection in Industrial Control Systems. AsiaCCS 2018: 525-536 - [c31]Wesley van der Lee, Sicco Verwer:
Vulnerability Detection on Mobile Applications Using State Machine Inference. EuroS&P Workshops 2018: 1-10 - [c30]Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Uzay Kaymak, Sicco Verwer:
Learning fuzzy decision trees using integer programming. FUZZ-IEEE 2018: 1-8 - 2017
- [j12]Sicco Verwer, Yingqian Zhang, Qing Chuan Ye:
Auction optimization using regression trees and linear models as integer programs. Artif. Intell. 244: 368-395 (2017) - [j11]Thijs Veugen, Jeroen Doumen, Zekeriya Erkin, Gaetano Pellegrino, Sicco Verwer, Jos H. Weber:
Improved privacy of dynamic group services. EURASIP J. Inf. Secur. 2017: 3 (2017) - [c29]Sicco Verwer, Yingqian Zhang:
Learning Decision Trees with Flexible Constraints and Objectives Using Integer Optimization. CPAIOR 2017: 94-103 - [c28]Rick Wieman, Mauricio Finavaro Aniche, Willem Lobbezoo, Sicco Verwer, Arie van Deursen:
An Experience Report on Applying Passive Learning in a Large-Scale Payment Company. ICSME 2017: 564-573 - [c27]Sicco Verwer, Christian A. Hammerschmidt:
flexfringe: A Passive Automaton Learning Package. ICSME 2017: 638-642 - [c26]Gaetano Pellegrino, Qin Lin, Christian A. Hammerschmidt, Sicco Verwer:
Learning behavioral fingerprints from Netflows using Timed Automata. IM 2017: 308-316 - [c25]Christian A. Hammerschmidt, Sebastian Garcia, Sicco Verwer, Radu State:
Reliable Machine Learning for Networking: Key Issues and Approaches. LCN 2017: 167-170 - [e1]Sicco Verwer, Menno van Zaanen, Rick Smetsers:
Proceedings of the 13th International Conference on Grammatical Inference, ICGI 2016, Delft, The Netherlands, October 5-7, 2016. JMLR Workshop and Conference Proceedings 57, JMLR.org 2017 [contents] - [i7]Xiaoran Liu, Qin Lin, Sicco Verwer, Dmitri Jarnikov:
Anomaly Detection in a Digital Video Broadcasting System Using Timed Automata. CoRR abs/1705.09650 (2017) - [i6]Alexis Linard, Rick Smetsers, Frits W. Vaandrager, Umar Waqas, Joost van Pinxten, Sicco Verwer:
Learning Pairwise Disjoint Simple Languages from Positive Examples. CoRR abs/1706.01663 (2017) - [i5]Christian A. Hammerschmidt, Radu State, Sicco Verwer:
Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms. CoRR abs/1707.09430 (2017) - 2016
- [c24]Christian A. Hammerschmidt, Samuel Marchal, Radu State, Sicco Verwer:
Behavioral clustering of non-stationary IP flow record data. CNSM 2016: 297-301 - [c23]Sicco Verwer, Menno van Zaanen, Rick Smetsers:
International Conference on Grammatical Inference 2016: Preface. ICGI 2016: 1-2 - [c22]Gaetano Pellegrino, Christian A. Hammerschmidt, Qin Lin, Sicco Verwer:
Learning Deterministic Finite Automata from Infinite Alphabets. ICGI 2016: 120-131 - [c21]Borja Balle, Rémi Eyraud, Franco M. Luque, Ariadna Quattoni, Sicco Verwer:
Results of the Sequence PredIction ChallengE (SPiCe): a Competition on Learning the Next Symbol in a Sequence. ICGI 2016: 132-136 - [c20]Christian A. Hammerschmidt, Samuel Marchal, Radu State, Gaetano Pellegrino, Sicco Verwer:
Efficient Learning of Communication Profiles from IP Flow Records. LCN 2016: 559-562 - [c19]Marcos L. P. Bueno, Arjen Hommersom, Peter J. F. Lucas, Sicco Verwer, Alexis Linard:
Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case. Probabilistic Graphical Models 2016: 50-61 - [i4]Rick Smetsers, Joshua Moerman, Mark Janssen, Sicco Verwer:
Complementing Model Learning with Mutation-Based Fuzzing. CoRR abs/1611.02429 (2016) - [i3]Christian Albert Hammerschmidt, Sicco Verwer, Qin Lin, Radu State:
Interpreting Finite Automata for Sequential Data. CoRR abs/1611.07100 (2016) - 2015
- [j10]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. Theory Pract. Log. Program. 15(6): 783-817 (2015) - 2014
- [j9]Sicco Verwer, Rémi Eyraud, Colin de la Higuera:
PAutomaC: a probabilistic automata and hidden Markov models learning competition. Mach. Learn. 96(1-2): 129-154 (2014) - [j8]Fides Aarts, Harco Kuppens, Jan Tretmans, Frits W. Vaandrager, Sicco Verwer:
Improving active Mealy machine learning for protocol conformance testing. Mach. Learn. 96(1-2): 189-224 (2014) - [j7]Anthony Labarre, Sicco Verwer:
Merging Partially Labelled Trees: Hardness and a DeclarativeProgramming Solution. IEEE ACM Trans. Comput. Biol. Bioinform. 11(2): 389-397 (2014) - [j6]Christophe Costa Florêncio, Sicco Verwer:
Regular inference as vertex coloring. Theor. Comput. Sci. 558: 18-34 (2014) - [c18]Rick Smetsers, Michele Volpato, Frits W. Vaandrager, Sicco Verwer:
Bigger is Not Always Better: on the Quality of Hypotheses in Active Automata Learning. ICGI 2014: 167-181 - [i2]Sicco Verwer, Yingqian Zhang, Qing Chuan Ye:
Learning optimization models in the presence of unknown relations. CoRR abs/1401.1061 (2014) - 2013
- [j5]Marijn Heule, Sicco Verwer:
Software model synthesis using satisfiability solvers. Empir. Softw. Eng. 18(4): 825-856 (2013) - [c17]Arjen Hommersom, Sicco Verwer, Peter J. F. Lucas:
Discovering Probabilistic Structures of Healthcare Processes. KR4HC/ProHealth 2013: 53-67 - [c16]Eduardo P. Costa, Sicco Verwer, Hendrik Blockeel:
Estimating Prediction Certainty in Decision Trees. IDA 2013: 138-149 - [c15]Sicco Verwer, Susan W. van den Braak, Sunil Choenni:
Sharing confidential data for algorithm development by multiple imputation. SSDBM 2013: 42:1-42:4 - [p2]Susan W. van den Braak, Sunil Choenni, Sicco Verwer:
Combining and Analyzing Judicial Databases. Discrimination and Privacy in the Information Society 2013: 191-206 - [p1]Sicco Verwer, Toon Calders:
Introducing Positive Discrimination in Predictive Models. Discrimination and Privacy in the Information Society 2013: 255-270 - [i1]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 abs/1309.6883 (2013) - 2012
- [j4]Sicco Verwer, Mathijs de Weerdt, Cees Witteveen:
Efficiently identifying deterministic real-time automata from labeled data. Mach. Learn. 86(3): 295-333 (2012) - [c14]Sicco Verwer, Yingqian Zhang:
Revenue prediction in budget-constrained sequential auctions with complementarities. AAMAS 2012: 1399-1400 - [c13]Christophe Costa Florêncio, Sicco Verwer:
Regular Inference as Vertex Coloring. ALT 2012: 81-95 - [c12]Faisal Kamiran, Asim Karim, Sicco Verwer, Heike Goudriaan:
Classifying Socially Sensitive Data Without Discrimination: An Analysis of a Crime Suspect Dataset. ICDM Workshops 2012: 370-377 - [c11]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: 14-25 - [c10]Yingqian Zhang, Sicco Verwer:
Mechanism for Robust Procurements. PRIMA 2012: 77-91 - [c9]Fides Aarts, Harco Kuppens, Jan Tretmans, Frits W. Vaandrager, Sicco Verwer:
Learning and Testing the Bounded Retransmission Protocol. ICGI 2012: 4-18 - [c8]Sicco Verwer, Rémi Eyraud, Colin de la Higuera:
Results of the PAutomaC Probabilistic Automaton Learning Competition. ICGI 2012: 243-248 - 2011
- [j3]Sicco Verwer, Mathijs de Weerdt, Cees Witteveen:
The efficiency of identifying timed automata and the power of clocks. Inf. Comput. 209(3): 606-625 (2011) - [c7]Sicco Verwer, Mathijs de Weerdt, Cees Witteveen:
Learning Driving Behavior by Timed Syntactic Pattern Recognition. IJCAI 2011: 1529-1534 - 2010
- [b1]Sicco Verwer:
Efficient Identification of Timed Automata: Theory and practice. Delft University of Technology, Netherlands, 2010 - [j2]Toon Calders, Sicco Verwer:
Three naive Bayes approaches for discrimination-free classification. Data Min. Knowl. Discov. 21(2): 277-292 (2010) - [c6]Ekaterina Vasilyeva, Mykola Pechenizkiy, Aleksandra Tesanovic, Evgeny Knutov, Sicco Verwer, Paul De Bra:
Towards EDM Framework for Personalization of Information Services in RPM Systems. EDM 2010: 331-332 - [c5]Marijn Heule, Sicco Verwer:
Exact DFA Identification Using SAT Solvers. ICGI 2010: 66-79 - [c4]Sicco Verwer, Mathijs de Weerdt, Cees Witteveen:
A Likelihood-Ratio Test for Identifying Probabilistic Deterministic Real-Time Automata from Positive Data. ICGI 2010: 203-216
2000 – 2009
- 2009
- [j1]Aneesh Sharma, Sicco Verwer:
Solution to exchanges 7.3 puzzle: product adoption in a social network. SIGecom Exch. 8(1) (2009) - [c3]Sicco Verwer, Mathijs de Weerdt, Cees Witteveen:
One-Clock Deterministic Timed Automata Are Efficiently Identifiable in the Limit. LATA 2009: 740-751 - 2008
- [c2]Sicco Verwer, Mathijs de Weerdt, Cees Witteveen:
Polynomial Distinguishability of Timed Automata. ICGI 2008: 238-251 - 2005
- [c1]Sicco Verwer, Mathijs de Weerdt, Cees Witteveen:
Timed Inference for Behavioral Pattern Recognition. BNAIC 2005: 291-296
Coauthor Index
Christian A. Hammerschmidt
aka: Christian Albert Hammerschmidt
aka: Christian Albert Hammerschmidt
Mathijs de Weerdt
aka: Mathijs Michiel de Weerdt
aka: Mathijs Michiel de Weerdt
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