Publications

Journal articles under review/revisions

  • Constructing classification trees using column generation (with Firat et al.). Download a working paper version via here
  • A group decision making approach for risk-based selection of pharmaceutical product shipment lanes (with Faghih et al.)
  • Regular Expression Inference based on Sample Augmentation and Common Substrings Extraction (with J. Guo)

Working paper

  • Data driven design for online industrial auctions. QC Ye, J Rhuggenaath, Y Zhang, S Verwer, MJ Hilgeman. 2019. Download via here

NEW in 2019

  • Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, and Uzay Kaymak, Remaining Useful Lifetime Prediction via Deep Domain Adaptation. Reliability Engineering and System Safety. Volume 195, 2020. Download via here
  • Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, and Uzay Kaymak, Attention Long Short-Term Memory Network for Remaining Useful Lifetime Predictions of Turbofan Engine Degradation. International journal of prognostics and health management. 2019
  • Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak. Optimal display ad allocation with guaranteed contracts and supply side platforms. Computers & Industrial Engineering. In Press. 2019. https://doi.org/10.1016/j.cie.2019.106071
  • Rowan Hoogervorst, Yingqian Zhang, Gamze Tillem, Zekeriya Erkin, and Sicco Verwer.  Optimization Under Privacy Preservation: Possibilities and Trade-offs. Information Sciences. Volume 500, pages 203-216.  download via here. https://doi.org/10.1016/j.ins.2019.05.011
  • Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang,
    Alp Akcay, Wan-Jui Lee, and Uzay Kaymak, Data driven policy on feasibility determination for train shunting problem, ECML PKDD 2019. download via here
  • Sicco Verwer and Yingqian Zhang. Learning optimal classification trees using a binary linear program formulation.  The 33rd AAAI Conference on Artificial Intelligence (AAAI 2019). download via here
  • Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, Uzay Kaymak. A heuristic policy for dynamic pricing and demand learning with limited price changes and censored demand. 2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
  • Dylan Rijnen, Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, and Yingqian Zhang. Machine Learning based Simulation Optimisation for Trailer Management. 2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC) . download via here
  • Jasper Paalman, Shantanu Mullick, Kalliopi Zervanou and Yingqian Zhang. Term Based Semantic Clusters for Very Short Text Classification. Recent Advances in Natural Language Processing (RANLP 2019)
  • Jason Rhuggenaath, Alp Akcay, Yingqian Zhang and Uzay Kaymak. A PSO-based Algorithm for Reserve Price Optimization in Online Ad Auctions. IEEE CEC 2019. download via here
  • Reza Refaei Afshar, Yingqian Zhang, Murat Firat and Uzay Kaymak. A Decision Support Method to Increase the Revenue of Ad Publishers in Waterfall Strategy. IEEE CIFEr 2019. download via here
  • Jason Rhuggenaath, Alp Akcay, Yingqian Zhang and Uzay Kaymak. Fuzzy Logic based Pricing combined with Adaptive Search for Reserve Price Optimization in Online Ad Auctions, FUZZ-IEEE 2019. download via here
  • Jason Rhuggenaath, Alp Akcay, Yingqian Zhang and Uzay Kaymak. Optimizing reserve prices for publishers in online ad auctions. IEEE CIFEr 2019. download via here
  • Arno Van De Ven, Yingqian Zhang, Wan-Jui Lee, Rik Eshuis, Anna Wilbik. Determining capacity of shunting yards by combining graph classification with local search. The Proceeding of 11th International Conference on Agents and Artificial Intelligence (ICAART 2019)(download via here)
  •  Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak. A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. The Proceeding of 11th International Conference on Agents and Artificial Intelligence (ICAART 2019).  (download via here)

Journal articles

  • Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, and Uzay Kaymak, Remaining Useful Lifetime Prediction via Deep Domain Adaptation. Reliability Engineering and System Safety. Volume 195, 2020. Download via here
  • Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, and Uzay Kaymak, Attention Long Short-Term Memory Network for Remaining Useful Lifetime Predictions of Turbofan Engine Degradation. International journal of prognostics and health management. 2019
  • Jason Rhuggenaath, Alp Akcay, Yingqian Zhang, Uzay Kaymak. Optimal display ad allocation with guaranteed contracts and supply side platforms. Computers & Industrial Engineering. In Press. 2019. https://doi.org/10.1016/j.cie.2019.106071
  • Rowan Hoogervorst, Yingqian Zhang, Gamze Tillem, Zekeriya Erkin, and Sicco Verwer.  Optimization Under Privacy Preservation: Possibilities and Trade-offs. Information Sciences. Volume 500, pages 203-216.  2019. download via here. https://doi.org/10.1016/j.ins.2019.05.011
  • Jun-Qiang Wang, Guo-Qiang Fan, Yingqian Zhang, Cheng-Wu Zhang, Joseph Y.-T. Leung, Two-agent scheduling on a single parallel-batching machine with equal processing time and non-identical job sizes, European Journal of Operational Research, Volume 258, Issue 2, 16 April 2017, Pages 478-490, ISSN 0377-2217, http://dx.doi.org/10.1016/j.ejor.2016.10.024. (Download)
    Keywords: Scheduling; Heuristics; Parallel-batching machine; Two-agent scheduling; NP-hardness
  • Qing Chuan Ye, Yingqian Zhang, Rommert Dekker, Fair task allocation in transportation. Omega. Volume 68, Pages 1-16. 2017. http://dx.doi.org/10.1016/j.omega.2016.05.005 (Impact Factor: 4.376) (Download)
  • Junqiang Wang, Jian Chen, Yingqian Zhang, George Q Huang,
    Schedule-based Execution Bottlenecks Identification in a Job Shop. Computers & Industrial Engineering. Volume 98, August 2016, Pages 308-322, ISSN 0360-8352. 2016. http://dx.doi.org/10.1016/j.cie.2016.05.039
    (Impact Factor: 1.783) (Download)
    Keywords: Job shop scheduling; Bottleneck identification; Execution bottlenecks; Multi-attribute evaluation
  • Sicco Verwer, Yingqian Zhang, Qing Chuan Ye, Auction optimization using regression trees and linear models as integer programs. Artificial Intelligence. Volume 244, pages 368–395, 2017  http://dx.doi.org/10.1016/j.artint.2015.05.004. Impact Factor: 3.371; AIS: 1.606. (Download)
  • Bart de Keijzer, Tomas Klos, Yingqian Zhang. Finding Optimal Solutions for Voting Game Design Problems. Journal of Artificial Intelligence Research. 50, 105-140, 2014. Impact Factor: 1.257; AIS: 1.167. (Download)
  • Jelmer P. Van der Gaast, Cornelieus A. Rietveld, Adriana F. Gabor, Yingqian Zhang. A Tabu Search Algorithm for application placement in computer clustering. Computers & Operations Research. 50, 38-46, 2014. Impact Factor: 1.861; AIS: 0.962. (Download)
  • Mathijs M. de Weerdt, Yingqian Zhang, and Tomas B. Klos. Multiagent Task Allocation in Social Networks. Autonomous Agents and Multi Agent Systems, Volume 25, Issue 1, pp 46-86, 2012. http://dx.doi.org/10.1007/s10458-011-9168-3. Impact Factor: 1.254; AIS: 0.74. (Download)
  • Yingqian Zhang, Efrat Manister, Sarit Kraus, V.S. Subrahmanian, and David Peleg. Computing the Fault Tolerance of Multiagent Deployment. Artificial Intelligence, 173(3-4):437-465, 2009. http://dx.doi.org/10.1016/j.artint.2008.11.007. Impact Factor: 3.371; AIS: 1.606. (Download)
  • Adriaan ter Mors, Chetan Yadati, Cees Witteveen, and Yingqian Zhang. Coordination by Design and the Price of Autonomy. Autonomous Agents and Multi Agent Systems. Volume 20, Issue 3, Page 308-341, 2010. http://dx.doi.org/10.1007/s10458-009-9086-9. Impact Factor: 1.254; AIS: 0.74. (Download)
  • Juergen Dix, Thomas Eiter, Michael Fink, Axel Polleres, and Yingqian Zhang. Monitoring Agents using Declarative Planning. Fundamenta Informaticae, 57(2-4) : 345-370, 2003.  Impact Factor: 0.717. (Download)

Book chapters

  • Yingqian Zhang and Sicco Verwer. Mechanism for Robust Procurements. I. Rahwan et al. (Eds.): Principles and Practice of Multi-Agent Systems. Lecture Notes in Computer Science LNCS 7455, pp. 77–91. Springer, Heidelberg. 2012. (Download)
  • Mengxiao Wu and Mathijs M. de Weerdt and Han La Poutre and Chetan Yadati and Yingqian Zhang and Cees Witteveen. Multi-player Multi-issue Negotiation with Complete Information. In Innovations in Agent-Based Complex Automated Negotiations Vol. 319. Studies in Computational Intelligence (pp. 147-159). Springer. 2011. ISBN 978-3-642-15612-0. (Download)
  • Mathijs de Weerdt and Yingqian Zhang. Preventing Under-Reporting in Social Task Allocation. Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis, Lecture Notes in Business Information Processing, Volume 44, 1-14. 2010. DOI: 10.1007/978-3-642-15237-5_1 (download)
  • Chetan Yadati, Cees Witteveen, and Yingqian Zhang. Improving task-based plan coordination. In Collaborative Agents — REsearch and Development (CARE). LNCS 6066, Volume 6066, 175-186. Springer, 2011. (Download)
  • Bart de Keijzer, Sylvain Bouveret, Tomas Klos, and Yingqian Zhang. On the complexity of efficiency and envy-freeness in fair division of indivisible goods with additive preferences. In Francesca Rossi and Alexis Tsoukias (Eds.). Algorithmic Decision Theory, pp. 98–110. Lecture Notes in Computer Science 5783, Springer, 2009. http://dx.doi.org/10.1007/978-3-642-04428-1_9. (Download)
  • J. Renze Steenhuisen, Cees Witteveen, and Yingqian Zhang. Plan coordination mechanisms and the price of autonomy. In Fariba Sadri and Ken Satoh, editors, Computational Logic in Multi-Agent Systems, LNCS 5056, pp 1-21. Springer Berlin/Heidelberg, 2008. (Download)
  • Juergen Dix and Yingqian Zhang, IMPACT: A multi-agent framework with declarative semantics, In Multi-Agent Programming: Languages, Platforms and Applications, Kluwer Academic Publishers, pp 69-94, 2005. ISBN 978-0-387-24568-3. (Download)
  • V. S. Subrahmanian, Sarit Kraus, and Yingqian Zhang. Distributed Algorithms for Dynamic Survivability of Multiagent Systems. In Computational Logic in Multi-Agent Systems, pp 1-15, LNCS 3259, Springer, 2004. ISBN 3-540-24010-1. (Download)
  • Juergen Dix, Thomas Eiter, Michael Fink, Axel Polleres, and Yingqian Zhang. Monitoring Agents using Declarative Planning. KI 2003:Advances in AI. A. Gunther, R. Kruse, B. Neumann (Eds.), LNCS 2821/2003, pp 646 – 660, Springer Berlin / Heidelberg, 2003. ISBN 978-3-540-20059-8. (Download)

(referred) Conference and workshop papers

  • Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang,
    Alp Akcay, Wan-Jui Lee, and Uzay Kaymak, Data driven policy on feasibility determination for train shunting problem, ECML PKDD 2019. download via here
  • Sicco Verwer and Yingqian Zhang. Learning optimal classification trees using a binary linear program formulation.  The 33rd AAAI Conference on Artificial Intelligence (AAAI 2019). download via here
  • Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, Alp Akcay, Yingqian Zhang, Uzay Kaymak. A heuristic policy for dynamic pricing and demand learning with limited price changes and censored demand. 2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
  • Dylan Rijnen, Jason Rhuggenaath, Paulo Roberto de Oliveira da Costa, and Yingqian Zhang. Machine Learning based Simulation Optimisation for Trailer Management. 2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC) . download via here
  • Jasper Paalman, Shantanu Mullick, Kalliopi Zervanou and Yingqian Zhang. Term Based Semantic Clusters for Very Short Text Classification. Recent Advances in Natural Language Processing (RANLP 2019)
  • Jason Rhuggenaath, Alp Akcay, Yingqian Zhang and Uzay Kaymak. A PSO-based Algorithm for Reserve Price Optimization in Online Ad Auctions. IEEE CEC 2019. download via here
  • Reza Refaei Afshar, Yingqian Zhang, Murat Firat and Uzay Kaymak. A Decision Support Method to Increase the Revenue of Ad Publishers in Waterfall Strategy. IEEE CIFEr 2019. download via here
  • Jason Rhuggenaath, Alp Akcay, Yingqian Zhang and Uzay Kaymak. Fuzzy Logic based Pricing combined with Adaptive Search for Reserve Price Optimization in Online Ad Auctions, FUZZ-IEEE 2019. download via here
  • Jason Rhuggenaath, Alp Akcay, Yingqian Zhang and Uzay Kaymak. Optimizing reserve prices for publishers in online ad auctions. IEEE CIFEr 2019. download via here
  • Arno Van De Ven, Yingqian Zhang, Wan-Jui Lee, Rik Eshuis, Anna Wilbik. Determining capacity of shunting yards by combining graph classification with local search. The Proceeding of 11th International Conference on Agents and Artificial Intelligence (ICAART 2019)(download via here)
  • Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak. A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. The Proceeding of 11th International Conference on Agents and Artificial Intelligence (ICAART 2019).  (download via here)
  • Rhuggenaath, J.S., Zhang, Y., Akcay, A., Kaymak, U. & Verwer, Sicco (2018). Learning fuzzy decision trees using integer programming. 2018 IEEE International Conference on Fuzzy Systems Piscataway: Institute of Electrical and Electronics Engineers Inc. (download via here)
  • Evertjan Peer, Vlado Menkovski, Yingqian Zhang, and Wan-Jui Lee. Shunting Trains with Deep Reinforcement Learning. The Proceeding of 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 (download via here )
  • Verwer S., Zhang Y. (2017) Learning Decision Trees with Flexible Constraints and Objectives Using Integer Optimization. In: Salvagnin D., Lombardi M. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2017. Lecture Notes in Computer Science, vol 10335. Springer, Cham. DOI:
    https://doi.org/10.1007/978-3-319-59776-8_8
  • Modeling participation behavior in repeated task allocations with fuzzy connectives, with Q. C. Ye, U. Kaymak. The Proceeding of 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC2017, pages 3219-3224. IEEE.
  • Max van de Westelaken and Yingqian Zhang. An Agent-Based Model for Feasibility and Diffusion of Crowd Shipping (extended abstract). Pages 419-420. BNAIC 2017. (download)
  • Qing Chuan Ye and Yingqian Zhang. Participation behavior and social welfare in repeated task allocations. IEEE International Conference on Agents. pp 94-97, IEEE, 2016. (Download)
  • Sicco Verwer and Yingqian Zhang. Revenue prediction in budget-constrained sequential auctions with complementarities (extended abstract). The Eleventh International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 2012.
  • Bart de Keijzer and Tomas Klos and Yingqian Zhang. Enumeration and exact design of weighted voting games. Proceedings of the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 391–398, 2010. http://ifaamas.org/Proceedings/aamas2010/pdf/01%20Full%20Papers/07_05_FP_0238.pdf
  • Chetan Yadati, Cees Witteveen and Yingqian Zhang. Coordinating Agents – An Analysis of Coordination in Supply-chain Management Tasks. In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence (ICAART). pp 218–223. INSTICC Press, 2010. (Download)
  • Yingqian Zhang and Mathijs M. de Weerdt. Creating Incentives to Prevent Intentional Execution Failures. Proceedings of the 2009 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, pages 431-434, IEEE, 2009. (Download)
  • Mengxiao Wu and Mathijs M. de Weerdt and Han La Poutre and Chetan
    Yadati and Yingqian Zhang and Cees Witteveen. Multi-player
    Multi-issue Negotiation with Complete Information. In Proceedings of the Second International Workshop on Agent-based Complex Automated Negotiations (ACAN). 2009. (Download)
  • Roman P.J. van der Krogt and Mathijs M. de Weerdt and Yingqian Zhang. Of Mechanism Design and Multiagent Planning. In Proceedings of the European Conference on Artificial Intelligence (ECAI-08), pp. 423-427, IOS Press, 2008. (Download)
  • Mathijs M. de Weerdt and Yingqian Zhang. Preventing Under-Reporting in Social Task Allocation. In Han La Poutre and Onn Shehory (Eds.). Proceedings of the 10th workshop on Agent-Mediated Electronic Commerce (AMEC-X). IFAAMAS, 2008.
  • Chetan Yadati, Cees Witteveen, Yingqian Zhang, Mengxiao Wu, and Han
    la Poutre. Autonomous Scheduling. In Proceedings of The 2008 International Conference on Foundations of Computer Science, pp 73–79. CSREA Press, 2008. (Download)
  • Mathijs M. de Weerdt, Yingqian Zhang, and Tomas B. Klos. Distributed Task Allocation in Social Networks. In Michael Huhns and Onn Shehory (Eds.). Proceedings of the 6th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’07), pp. 488–495. Research Publishing Services. 2007. (Download)
  • Chetan Yadati, Cees Witteveen, Yingqian Zhang, Mengaxiao Wu and Han la Poutre. Autonomous Scheduling with unbounded and bounded agents. In Proceedings of the sixth German Conference on Multi-Agent system Technologies (MATES). 2008. (Download). Best Paper Award
  • Yingqian Zhang and Mathijs M. de Weerdt. VCG-based Truthful Mechanisms for Social Task Allocation. In Proceedings of the Fifth European Workshop on Multi-Agent Systems (EUMAS-07), pp. 378 — 394, 2007. (Download)
  • Yingqian Zhang, Efrat Manister, Sarit Kraus, V.S. Subrahmanian. Approximation Results for Probabilistic Survivability. Proc. of the Second IEEE Symposium on Multi-Agent Security and Survivability (MAS&S 2005), Philadelphia, PA, pp. 1–10, IEEE Computer Society, 2005. ISBN:0-7803-9447-X.  Best Paper Award. (Download)
  • Yingqian Zhang. Towards Fault Tolerance in MASs, The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’05), pp. 1387, ACM. 2005. (Download)
  • Juergen Dix, Thomas Eiter, Michael Fink, Axel Polleres, Yingqian Zhang, Monitoring Agents using Declarative Planning. KI 2003, Advances in AI. A.Gunther, R. Kruse, B. Neumann (Eds.), pp 490–504, 2003
  • Yingqian Zhang and Lai-Wan Chan. ForeNet: Fourier Recurrent Networks for Time Series Prediction, In Proceedings of International Conference on Neural Information Processing, ICONIP 2000, Korea, pp 576 – 582, 2000. (Download)
  • Yingqian Zhang, Jiuqiu Feng and Hui Li, Application of Neural Network in the Prediction of China Stock Market. In Proceedings of International Symposium on Intelligent Data Engineering and Learning, Hong Kong (IDEAL98), China, pp 179 -185, 1998.