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The Computer Science Journal (https://journals.agh.edu.pl/csci/) is published by the AGH University of Science and Technology, Krakow, Poland. The Editors of the Journal are members of the Faculty of Computer Science, Electronics and Telecommunications and the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. The Editorial Board consists of many renowned researchers from all over the world.

Original papers on theoretical and applied computer science problems are published. Example areas of interest are: theoretical aspects of computer science, pattern recognition and processing, evolutionary algorithms, neural networks, multi-agent systems, computer networks management, distributed, grid and cloud computing.

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2017

  1. I. Schlotter, P. Faliszewski, E. Elkind, Campaign Management Under Approval-Driven Voting Rules, Algorithmica, Vol. 77(1), pp. 84-115, 2017.
  2. P. Faliszewski, J. Sawicki, R. Schaefer, M. Smółka, Multiwinner Voting in Genetic Algorithms, IEEE Intelligent Systems, Vol. 32(1), pp. 40-48, 2017.
  3. E. Elkind, P. Faliszewski, J.-F. Laslier, P. Skowron, A. Slinko, N. Talmon, What Do Multiwinner Voting Rules Do? An Experiment Over the Two-Dimensional Euclidean Domain, Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, pp. 494--501, February 2017.
  4. J. Kudzia, R. Słota, T. Lichoń, M. Wrzeszcz, Ł. Dutka, R. G. Słota, J. Kitowski, Using Onedata for Global Sharing and Processing of Legacy Large Data Sets, in: KU KDM 2017 : tenth ACC Cyfronet AGH users' conference : Zakopane, 8-10 Mar, 2017 : proceedings. — Kraków : ACK Cyfronet AGH, [2017], pp. 49-50
  5. D. Król, R. Słota, J. Kitowski, Parameter studies on heterogeneous computing infrastructures with the Scalarm platform, in: KU KDM 2017 : tenth ACC Cyfronet AGH users' conference : Zakopane, 8-10 Mar, 2017 : proceedings. — Kraków : ACK Cyfronet AGH, [2017], pp. 55-56
  6. E. Elkind, P. Faliszewski, P. Skowron, A. Slinko, Properties of Multiwinner Voting Rules, Social Choice and Welfare, Vol. 48(3), pp. 599--632, 2017.
  7. J. Sawicki, M. Smolka, M. Los, R. Schaefer, P. Faliszewski, Two-Phase Strategy Managing Insensitivity in Global Optimization, in proceedings of EvoApplications, pp. 266--281, April 2017.
  8. K. Magiera, P. Faliszewski, How hard is control in single-crossing elections?, Autonomous Agents and Multiagent Systems, Vol. 31(3), pp. 606--627, 2017
  9. W. Dzwinel, R. Wcisło, W. Czech,  A fast force-directed method for interactive visualization of complex networks, Journal of Computational Science 20 (1), April 2017, pp. 448–459
  10. W. Dzwinel, A. Kłusek, M. Paszyński, A concept of a prognostic system for personalized anti-tumor therapy based on supermodeling, International Conference on Computational Science ICCS 2017, Zurich, Procedia Computer Science. 108C. . 10.1016/j.procs.2017.05.013.
  11. W. Czech, W. Mielczarek, W. Dzwinel, Distributed computing of distance‐based graph invariants for analysis and visualization of complex network, Concurrency and Computation Practice and Experience 29(9),  April 2017, pp. 1–21
  12. W. Dzwinel, R. Wcisło, M. Strzoda, Visualization of the network of historical events, 13h International Conference on Machine Learning and Data Mining MLDM, New York , July 15-20, 2017, working paper
  13. M. Łoś, M. Paszyński, A. Kłusek, W. Dzwinel, Application of fast isogeometric L2 projection solver for tumor growth simulations, Computer Methods in Applied Mechanics and Engineering, vol. 316 · January 2017, pp 1257–1269
  14. W. Dzwinel, A. Kłusek, O. V. Vasilyev, Supermodeling in Simulation of Melanoma Progression, in: proc. of The International Conference on Computational Science (ICCS 2016), Volume 80, Procedia Computer Science, 2016, pp. 999–1010
  15. M. Antkiewicz, M. Kuta, J.  Kitowski, Author Profiling with Classification Restricted Boltzmann Machines, in: L .Rutkowski,  M. Korytkowski, R. Scherer, R. Tadeusiewicz, Ryszard, L. A. Zadeh, J. M. Zurada (eds), proc. of Artificial Intelligence and Soft Computing: 16th International Conference, ICAISC 2017, Zakopane, Poland, June 11-15, 2017,  LNAI vol. 10245, Springer, 2017
  16. D. Bachniak, Ł. Rauch, D. Król, J. Liput, R. Słota, J. Kitowski, M. Pietrzyk, Sensitivity analysis on HPC systems with Scalarm platform, Concurrency Computat.: Pract. Exper. 2017; 29:e4025, pubblished on-line, 10.1002/cpe.4025
  17. P. Faliszewski, P. Skowron, N. Talmon, Bribery as a Measure of Candidate Success: Complexity Results for Approval-Based Multiwinner Rules, in proceedings of AAMAS-2017, Maj 2017, pp. 6-14.
  18. W. Dzwinel, A. Kłusek, M. Paszyński, A concept of a prognostic system for A concept of a prognostic system for personalized anti-tumor therapy based on supermodeling, in: proc. of International Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland, Procedia Computer Science, 108C (2017), pp. 1832–1841
  19. B. Baliś , M. Bubak , D. Haręźlak , P. Nowakowski , M.Pawlik, B. Wilk, Towards an operational database for real-time environmental early warning systems, in: proc. of International Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland, Procedia Computer Science, 108C (2017), pp 2250–2259
  20. B, Baliś, T. Bartyński, M. Bubak, D. Haręźlak, M. Kasztelnik, M. Malawski, P. Nowakowski, M. Pawlik, B. Wilk, Smart levee monitoring and flood decision support system: reference architecture computing management, in: proc. of International Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland, Procedia Computer Science, 108C (2017), pp. 2220–2229
  21. M. Wrzeszcz, Ł. Opioła, K. Zemek, B. Kryza, Ł. Dutka, R. Słota, J. Kitowski, Effective and Scalable Data Access Control in Onedata Effective and Scalable Data Control in Onedata Large Distributed Virtual File System, in: proc. of International Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland, Procedia Computer Science, 108C (2017), pp. 445-454
  22. L. Kangkang, M. Malawski, J. Nabrzyski, Topology-aware Topology-aware Job Hard Allocation in 3D Torus-based HPC Systems with Job Priority Constraints in: proc. of International Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland, Procedia Computer Science, 108C (2017), pp. 515–524
  23. H. Aziz, E. Elkind, P. Faliszewski, M. Lackner, P. Skowron, The Condorcet Principle for Multiwinner Elections: From Shortlisting to Proportionality, in Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-2017), pp. 84--90, August 2017.
  24. P. Faliszewski, P. Skowron, A. Slinko, N. Talmon, Multiwinner Rules on Paths From k-Borda to Chamberlin-Courant, in Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-2017), pp. 192--198, August 2017.
  25. K. Magiera, P. Faliszewski, Recognizing Top-Monotonic Preference Profiles in Polynomial Time, in Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-2017), pp. 324--330, August 2017.
  26. P. Faliszewski, Committee Scoring Rules: A Call to Arms, in Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-2017), pp. 5121--5125, August 2017
  27. R. Bredereck, P. Faliszewski, A. Kaczmarczyk, R. Niedermeier, P. Skowron, N. Talmon, Robustness Among Multiwinner Voting Rules, in Proceedings of the Tenth International Symposium on Algorithmic Game Theory (SAGT-2017), pp. 80--92, September 2017
  28. M. Kuta, M. Morawiec, J. Kitowski, Sentiment Analysis with Tree-Structured Gated Recurrent Units, . In: Ekštein K., Matoušek V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science, vol 10415. Springer, Cham, 2017, pp 74-82
  30. W. Dzwinel, R.  Wcisło, S. Matwin, ivhd: A fast and simple algorithm for embedding large and high-dimensional data. 2017 . 10.13140/RG.2.2.28959.15520/2
  31. W. Dzwinel, R. Wcisło,  ivhd: A robust linear-time and memory efficient method for visual exploratory data analysis, in: P. Perner (ed.), proc.  of Machine learning and data mining in pattern recognition : 13th international conference : MLDM 2017, New York, NY, USA, July 15–20, 2017, LNCC 10358, Springer 2017, pp. 345–360
  32. W. Dzwinel, R. Wcisło, M. Strzoda, ivga: Visualization of the network of historical events. 2017 (working paper)
  33. W. Dzwinel, R. Wcisło, W. Czech, Ivga: A fast force-directed method for interactive visualization of complex networks. Journal of Computational Science. 21. 2017, pp. 448-459. 10.1016/j.jocs.2016.09.001
  34. W. Dzwinel, A. Kłusek, R. Wcisło, M. Panuszewska, P. Topa, Continuous and discrete models of melanoma progression simulated in multi-GPU environment. 2017 . 10.13140/RG.2.2.35287.68007
  35. A. H. Eckes, T. Gubała, P. Nowakowski, T. Szymczyszyn, R. Wells, J. A. Irwin, C. Horro, J. M. Hancock, G. King, S. C. Dyer, W. Jurkowski: Introducing the Brassica Information Portal: Towards integrating genotypic and phenotypic Brassica crop data [version 1; referees: 3 approved]. F1000Research 2017, 6:465 (doi: 10.12688/f1000research.11301.1) (2017)
  36. D. Król, R. F. da Silva, E. Deelman, V. E. Lynch, Workflow Performance Profiles: Development and Analysis, in: F. Desprez, P.-F. Dutot, et al. (Eds.), proc. of Euro-Par 2016 International Workshops, Grenoble, France, August 24-26, 2016, LNCS 10104, Springer, 2017, pp. 108-120
  37. P. Faliszewski, P. Skowron, A. Slinko, N. Talmon. Multiwinner Voting: A New Challenge for Social Choice Theory. In Ulle Endriss (editor), Trends in Computational Social Choice, chapter 2, pages 27–47. AI Access, 2017.
  38. P. Skowron, P. Faliszewski, Chamberlin--Courant Rule with Approval Ballots: Approximating the MaxCover Problem with Bounded Frequencies in FPT Time, Journal of Artificial Intelligence Research, Vol. 60, pp. 687--716, 2017.
  39. J. Chen, P. Faliszewski, R. Niedermeier, N. Talmon, Elections with Few Voters: Candidate Control Can Be Easy, Journal of Artificial Intelligence Research, Vol. 60, pp. 937--1002, 2017.
  40. D. Baumeister, P. Faliszewski, A. Laruelle, T. Walsh, Voting: Beyond Simple Majorities and Single-Winner Elections (Dagstuhl Seminar 17261), Dagstuhl Reports Vol. 7(6). pp. 109--134, 2017
  41. M. Wrzeszcz, J. Koźlak, J. Kitowski, Modelling Agents Cooperation Through Internal Visions of Social Network and Episodic Memory, Computing and Informatics, Vol. 36, 2017, pp. 86–112, doi: 10.4149/cai 2017 1 86
  42. W. Dzwinel, A novel linear-time and memory saving approach for visual exploratory data analysis: data embedding and graph visualization, 4th international conference on BigData analysis and data mining, September 07–08, 2017, Paris, France (online source)
  43. P. Faliszewski, How to choose a committee based on agents' preferences?, in Proceedings of the 4th International Conference on Behavioral, Economic, Socio-cultural Computing (BESC), October 2017
  44. M. Piwowar, E. Matczynska, M. Malawski, T. Szapieniec, I. Roterman-Konieczna, Genetic traces of never born proteins. Bio-Algorithms and Med-Systems 13(2): 79 (2017)
  45. M. Kasztelnik, E. Coto, M. Bubak, M. Malawski, P. Nowakowski, J. Arenas, A. Saglimbeni, D. Testi, A. F. Frangi, Support for Taverna workflows in the VPH-Share cloud platform. Computer Methods and Programs in Biomedicine 146: 37-46 (2017)
  46. B. Balis, K. Figiela, K. Jopek, M. Malawski, M. Pawlik, Porting HPC applications to the cloud: A multi-frontal solver case study. J. Comput. Science 18: 106-116 (2017)
  47. M. Malawski, K. Figiela, A. Gajek, A. Zima, Benchmarking Heterogeneous Cloud Functions. In Dora Blanca Heras, Luc Bougé, Gabriele Mencagli, Emmanuel Jeannot, Rizos Sakellariou, Rosa M. Badia, Jorge G. Barbosa, Laura Ricci, Stephen L. Scott, Stefan Lankes, Josef Weidendorfer (eds): Euro-Par 2017: Parallel Processing Workshops - Euro-Par 2017 International Workshops, Santiago de Compostela, Spain, August 28-29, 2017, Revised Selected Papers. Lecture Notes in Computer Science 10659, Springer 2018, ISBN 978-3-319-75177-1 2017: 415-426
  48. K. Li, M. Malawski, J. Nabrzyski: Reducing Fragmentation on 3D Torus-Based HPC Systems Using Packing-Based Job Scheduling and Job Placement Reconfiguration. ISPDC 2017: 34-43
  49. K. Bzowski, J. Kitowski,, R. Kuziak , P. Uranga, I Gutierrez, R. Jacolot , Ł. Rauch, M. Pietrzyk, Development of the Material Database for The Virtroll Computer System Dedicated to Design Of An Optimal Hot Strip Rolling Technology, Computer Methods in Materials Science, Vol. 17, 2017, No. 4, Publishing House AKAPIT, pp. 225 – 246
  50. A. Kłusek, Tumor simulation by using supermodeling – an example of a new concept of data assimilation in modeling of complex systems , in:  W. K. V. Chan, [et al. eEds.),  Proceedings of the Winter Simulation Conference 2017,  3–6 December 2017, Las Vegas, USA, IEEE, 2017, electronic document, access since 2017,  pp. 4640–4641
  51. P. I. Wójcik, M. Kurdziel "Random projection initialization for deep neural networks", 25th European Symposium on Artificial Neural Networks, 111-116, 2017, http://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2017-43.pdf
  52. K. Grzegorczyk, M. Kurdziel "Binary Paragraph Vectors", Proceedings of the 2nd Workshop on Representation Learning for NLP (Rep4NLP@ACL), 121--130, 2017, Association for Computational Linguistics, http://aclweb.org/anthology/W17-2615
  53. W. Funika, P. Koperek, J. Kitowski, Towards Stable Co-evolution of Deep Neural Networks and Fitness Predictors, in: M. Bubak, M. Turała, K. Wiatr (Eds.), Proceedings of Cracow Grid Workshop - CGW'17, October 23-25 2017, ACC-Cyfronet AGH, 2017, Krakow

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