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Representative papers:

DEPARTMENT OF THEORETICAL FOUNDATIONS OF COMPUTER SCIENCE

THEORY OF DISTRIBUTED AND COMPUTING SYSTEMS
  1. Wojciech Jamroga, Michał Knapik, Damian Kurpiewski, Łukasz Mikulski: Approximate verification of strategic abilities under imperfect information, in: Artificial Intelligence, 2019, Vol. 277 (art. 103172), pp. 1-30
  2. Francesco Belardinelli, Wojciech Jamroga, Damian Kurpiewski, Vadim Malvone, Aniello Murano: Strategy Logic with Simple Goals: Tractable Reasoning about Strategies, in: Sarit Kraus (eds.): Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, International Joint Conferences on Artificial Intelligence, 2019, ISBN: 978-0-9992411-4-1, pp. 88-94
  3. Ivanoe De Falco, Eryk Laskowski, Richard Olejnik, Umberto Scafuri, Ernesto Tarantino, Marek Tudruj: Parallel extremal optimization in processor load balancing for distributed applications, in: Applied Soft Computing, 2016, Vol. 46, pp.187-203
  4. Wojciech Jamroga, Wojciech Penczek, Teofil Sidoruk, Piotr Dembiński, Antoni Mazurkiewicz: Towards Partial Order Reductions for Strategic Ability, in: Journal of Artificial Intelligence Research, 2020, Vol. 68, pp. 817-850
  5. Laure Petrucci, Michał Knapik, Wojciech Penczek, Teofil Sidoruk: Squeezing State Spaces of (Attack-Defence) Trees, in: Jun Pang, Jing Sun (eds.): 24th International Conference on Engineering of Complex Computer Systems, ICECCS 2019, Guangzhou, China, November 10-13, 2019, IEEE Computer Society Press, 2019, ISBN: 978-1-7281-4646-1, pp. 71-80
  6. Łukasz Maśko, Marek Tudruj: Application global state monitoring in optimization of parallel event-driven simulation, in: Concurrency and Computation-Practice & Experience, Vol. 31(19), 2019, pp.e5015:1-14
  7. Włodzimierz Drabent: Correctness and Completeness of Logic Programs, in: ACM Transactions on Computational Logic, 2016, Vol. 17 (3), pp.1-32
  8. Wojciech Jamroga, Beata Konikowska, Damian Kurpiewski, Wojciech Penczek: Multi-valued Verification of Strategic Ability, in: Fundamenta Informaticae, 2020, Vol. 175 (1-4), pp. 207-251
CRYPTOGRAPHY
  1. Seyit Camtepe, Jarek Duda, Arash Mahboubi, Paweł Morawiecki, Surya Nepal, Marcin Pawlowski, Józef Pieprzyk: ANS-based compression and encryption with 128-bit security, in: International Journal of Information Security, Vol. 21 (5), pp. 1051–1067
  2. Seyit Camtepe, Jarek Duda, Arash Mahboubi, Paweł Morawiecki, Surya Nepal, Marcin Pawlowski, Józef Pieprzyk: Compcrypt - Lightweight ANS-based Compression and Encryption, in: Cryptology ePrint Archive: Report 2021/010, International Association for Cryptologic Research, pp. 1-20
  3. Mohammad Ali Orumiehchiha, Saeed Rostami, Elham Shakour, Józef Pieprzyk: A differential fault attack on the WG family of stream ciphers, in: Journal of Cryptographic Engineering, 2020, Vol. 10 (2), pp. 189-195
  4. MHuy Quoc Le, Dung Hoang Duong, Willy Susilo, Ha Thanh Nguyen Tran, Viet Cuong Trinh, Józef Pieprzyk, Thomas Plantard: Lattice Blind Signatures with Forward Security, in: Joseph Liu, Hui Cui (eds.): Information Security and Privacy. 25th Australasian Conference, ACISP 2020, Perth, WA, Australia, November 30 – December 2, 2020, Proceedings, Springer International Publishing, Lecture Notes in Computer Science, Vol. 12248, 2020, ISBN: 978-3-030-55303-6, pp. 3-22
  5. Hong Lai, Józef Pieprzyk, Lei Pan: Analysis of Weighted Quantum Secret Sharing based on Matrix Product States, in: Quantum Information Processing, 2020, Vol. 19 (12), pp. 418:1-16
  6. Paweł Morawiecki, Przemysław Spurek, Marek Śmieja, Jacek Tabor: Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models, in: ESANN 2020 proceedings, 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Online event, 2-4 October 2020, 2020, ISBN: 978-2-87587-074-2, pp. 55-60
  7. Cong Zuo, Shifeng Sun, Joseph K. Liu, Jun Shao, Józef Pieprzyk: Dynamic Searchable Symmetric Encryption with Forward and Stronger Backward Privacy, in: Computer Security – ESORICS 2019. 24th European Symposium on Research in Computer Security, Luxembourg, September 23–27, 2019, Proceedings, Part II, Springer International Publishing, Lecture Notes in Computer Science, Vol. 11736, 2019, ISBN: 978-3-030-29961-3, pp. 283-303
  8. Ashutosh Dhar Dwivedi, Paweł Morawiecki, Gautam Srivastava: Differential Cryptanalysis of Round-Reduced SPECK suitable for Internet of Things devices, in: IEEE Access, 2019, Vol. 7 (2019), pp. 16476-16486
  9. Ashutosh Dhar Dwivedi, Paweł Morawiecki, Rajani Singh, Shalini Dhar: Differential-linear and related key cryptanalysis of round-reduced scream, in: Information Processing Letters, 2018, Vol. 136, pp. 5-8
  10. Cong Zuo, Shi-Feng Sun, Joseph Liu, Jun Shao, Józef Pieprzyk: Dynamic Searchable Symmetric Encryption Schemes Supporting Range Queries with Forward (and Backward) Security, in: Javier Lopez, Jianying Zhou, Miguel Soriano (eds.): Computer Security. 23rd European Symposium on Research in Computer Security, ESORICS 2018, Barcelona, Spain, September 3-7, 2018, Proceedings, Part II, Springer International Publishing, Lecture Notes in Computer Science, Vol. 11099, 2018, ISBN: 978-3-319-98988-4, pp. 228-246
  11. Paweł Morawiecki, Józef Pieprzyk, Marian Srebrny, Michal Straus: Cube Attacks and Cube-Attack-Like Cryptanalysis on the Round-Reduced Keccak Sponge Function, in: Advances in Cryptology -- EUROCRYPT 2015. 34th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Sofia, Bulgaria, April 26-30, 2015, Proceedings, Part I, Springer International Publishing, Lecture Notes in Computer Science, Vol. 9056, 2015, ISBN: 978-3-662-46799-2, pp. 733-761

DEPARTMENT OF ARTIFICIAL INTELLIGENCE

FOUNDATIONS OF ARTIFICIAL INTELLIGENCE
  1. Robert Kłopotek, Mieczysław A. Kłopotek, Sławomir T. Wierzchoń: A feasible k-means kernel trick under non-Euclidean feature space, in: International Journal of Applied Mathematics and Computer Science, 2020, Vol. 30 (4), pp. 703-715
  2. Małgorzata Lucińska, Sławomir T. Wierzchoń: Clustering based on eigenvectors of the adjacency matrix, in: International Journal of Applied Mathematics and Computer Science, 2018, Vol. 28 (4), pp. 771-786
  3. Mieczysław A. Kłopotek: On the Consistency of k-means++ algorithm, in: Fundamenta Informaticae, 2020, Vol. 172 (4), pp. 361-377
  4. Mieczysław A. Kłopotek: An Aposteriorical Clusterability Criterion for k-Means++ and Simplicity of Clustering, in: SN Computer Science, 2020, Vol. 1, art. no 80 pp. 1-38
  5. Dariusz Czerski, Paweł Łoziński, Mieczysław A. Kłopotek, Bartłomiej Starosta, Marcin Sydow: FlexTrustRank: A New Approach to Link Spam Combating, in: Leszek Rutkowski, others (eds.): Artificial Intelligence and Soft Computing 19th International Conference, ICAISC 2020, Zakopane, Poland, October 12-14, 2020, Proceedings, Part II, Springer International Publishing, Lecture Notes in Artificial Intelligence, Vol. 12416, 2020, ISBN: 978-3-030-61533-8, pp. 130-139
  6. Magdalena Kacprzak, Bartłomiej Starosta, Katarzyna Wȩgrzyn-Wolska: New Approach to Decision Making, in: Ajith Abraham, Katarzyna Wegrzyn-Wolska, Aboul Ella Hassanien, Vaclav Snasel, Adel M. Alimi (eds.): Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015, 2016, Advances in Intelligent Systems and Computing, Vol. 427, ISBN: 978-3-319-29503-9, pp. 397-407
  7. Piotr Borkowski, Krzysztof Ciesielski, Mieczysław A. Kłopotek: Semantic Classifier Approach to Document Classification, in: Leszek Rutkowski, others (eds.): Artificial Intelligence and Soft Computing 19th International Conference, ICAISC 2020, Zakopane, Poland, October 12-14, 2020, Proceedings, Part I, Springer International Publishing, Lecture Notes in Artificial Intelligence, Vol. 12415, 2020, ISBN: 978-3-030-61400-3, pp. 657-667
  8. Piotr Borkowski, Krzysztof Ciesielski, Mieczysław A. Kłopotek: The Impact of Supercategory Inclusion on Semantic Classifier Performance, in: Martin Stettinger, Gerhard Leitner, Alexander Felfernig, Zbigniew W. Ras (eds.): Intelligent Systems in Industrial Applications, Springer International Publishing, Studies in Computational Intelligence, Vol. 949, 2021, ISBN: 978-3-030-67590-5, pp. 69-79
  9. Mieczysław A. Kłopotek: Machine learning friendly set version of Johnson–Lindenstrauss lemma, in: Knowledge and Information Systems, 2020, Vol. 62 (5), pp. 1961-2009
  10. Sławomir T. Wierzchoń, Mieczysław A. Kłopotek: Modern Algorithms of Cluster Analysis, Springer International Publishing, 2018, 978-3-319-69307-1, 421 p.
  11. Steffen Metzger, Ralf Schenkel, Marcin Sydow: QBEES: query-by-example entity search in semantic knowledge graphs based on maximal aspects, diversity-awareness and relaxation, in: Journal of Intelligent Information Systems, 2017, Vol. 49 (3), pp. 333-366
  12. Marcin Sydow: Approximation Guarantees for Max Sum and Max Min Facility Dispersion with Parameterised Triangle Inequality and Applications in Result Diversification, in: Mathematica Applicanda, 2014, Vol. 42 (2), pp. 241-257
  13. Magdalena Kacprzak, Bartłomiej Starosta: Two Approaches to Fuzzy Implication, rozdział in: Piotr Prokopowicz, Jacek Czerniak, Dariusz Mikołajewski, Łukasz Apiecionek, Dominik Ślȩzak (eds.): Theory and Applications of Ordered Fuzzy Numbers. A Tribute to Professor Witold Kosiński, Springer International Publishing, 2017, ISBN: 978-3-319-59613-6, Studies in Fuzziness and Soft Computing, Vol. 356, pp. 133-154
LINGUISTIC ENGINEERING
  1. Agnieszka Patejuk, Adam Przepiórkowski: Predicative Adverbs: Evidence from Polish, in: Linguistic Inquiry, 2020, doi: 10.1162/ling_a_00394, pp. 1-22
  2. Piotr Przybyła: Capturing the Style of Fake News, in: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence. February 7–12, 2020, New York, New York, USA, AAAI Press, Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 34, 2020, ISBN: 978-1-57735-835-0, pp. 490-497
  3. Katarzyna Krasnowska-Kieraś, Alina Wróblewska: Empirical Linguistic Study of Sentence Embeddings, in: Anna Korhonen, David Traum, Lluís Màrquez (eds.): Proceedings of the 57th Conference of the Association for Computational Linguistics. July 28 - August 2, 2019 Florence, Italy, Association for Computational Linguistics, 2019, ISBN: 978-1-950737-48-2, pp. 5729-5739
  4. Maciej Ogrodniczuk: Nominal coreference resolution for Polish, in: Poznan Studies in Contemporary Linguistics, 2019, Vol. 55 (2), pp. 367-396
  5. Aleksander Wawer: Sentiment Analysis for Polish, in: Poznan Studies in Contemporary Linguistics, 2019, Vol. 55 (2), pp. 445-468
  6. Marcin Woliński: Automatyczna analiza składnikowa języka polskiego, Wydawnictwa Uniwersytetu Warszawskiego, 2019, 978-83-235-3606-2, 290 p.
  7. Witold Kieraś, Łukasz Kobyliński, Maciej Ogrodniczuk: Korpusomat – a Tool for Creating Searchable Morphosyntactically Tagged Corpora, in: Computational Methods in Science and Technology, 2018, Vol. 24 (1), pp. 21-27
  8. Agnieszka Mykowiecka, Małgorzata Marciniak, Piotr Rychlik: Recognition of irrelevant phrases in automatically extracted lists of domain terms, in: Terminology, 2018, Vol. 24 (1), pp. 66-90
  9. Adam Przepiórkowski, Agnieszka Patejuk: Arguments and Adjuncts in Universal Dependencies, in: Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018), 2018, pp. 3837-3852
  10. Małgorzata Marciniak, Agnieszka Mykowiecka, Piotr Rychlik: Automatyczne wydobywanie terminologii dziedzinowej z korpusów tekstowych, in: Język Polski, 2017, Vol. XCVII (1), pp. 64-74
  11. Adam Przepiórkowski, Elżbieta Hajnicz, Anna Andrzejczuk, Agnieszka Patejuk, Marcin Woliński: Walenty: gruntowny składniowo-semantyczny słownik walencyjny języka polskiego, in: Język Polski, 2017, Vol. XCVII (1), pp. 29–46
STATISTICAL ANALYSIS AND MODELLING
  1. Łukasz Jerzy Dębowski: Information Theory Meets Power Laws: Stochastic Processes and Language Models, Wiley & Sons, 2020, 978-1-119-62536-0, 384 p.
  2. Łukasz Jerzy Dębowski: Maximal Repetition and Zero Entropy Rate, in: IEEE Transactions on Information Theory, 2018, Vol. 64 (4), pp. 2212-2219
  3. Krzysztof Rudaś, Szymon Jaroszewicz: Linear regression for uplift modeling, in: Data Mining and Knowledge Discovery, 2018, Vol. 32 (5), pp. 1275-1305
  4. Barbara Żogała-Siudem, Szymon Jaroszewicz: Fast stepwise regression based on multidimensional indexes, in: Information Sciences, 2021, Vol. 549, pp. 288-309
  5. Mariusz Kubkowski, Jan Mielniczuk, Paweł Teisseyre: How to Gain on Power: Novel Conditional Independence Tests Based on Short Expansion of Conditional Mutual Information, in: Journal of Machine Learning Research, 2021, Vol. 22, pp. 62:1-57
  6. Małgorzata Łazęcka, Jan Mielniczuk: Analysis of Information-Based Nonparametric Variable Selection Criteria, in: Entropy, 2020, Vol. 22 (9), pp. 974:1-18
  7. Mariusz Kubkowski, Jan Mielniczuk: Selection Consistency of Lasso-Based Procedures for Misspecified High- Dimensional Binary Model and Random Regressors, in: Entropy, 2020, Vol. 22 (2), pp. 153:1-29
  8. Jan Mielniczuk, Paweł Teisseyre: Stopping rules for mutual information-based feature selection, in: Neurocomputing, 2019, Vol. 358, pp. 255-274
  9. Paweł Teisseyre, Damien Zufferey, Marta Słomka: Cost-sensitive classifier chains: Selecting low-cost features in multi-label classification, in: Pattern Recognition, 2019, Vol. 86, pp. 290-319
  10. Dariusz Kalociński, Tomasz Steifer: An Almost Perfectly Predictable Process with No Optimal Predictor, in: 2019 IEEE International Symposium on Information Theory (ISIT), Proceedings, July 7–12, 2019, La Maison de La Mutualité, Paris, France, Institute of Electrical and Electronics Engineers, 2019, ISBN: 978-1-5386-9291-2, pp. 2504-2508
COMPUTATIONAL BIOLOGY
  1. Karolina Stępniak, Magdalena A. Machnicka, Jakub Mieczkowski, Anna Macioszek, Bartosz Wojtaś, (...), Malgorzata Perycz, (...), Michał J. Dąbrowski, Michał Dramiński, Marta Jardanowska, Ilona Grabowicz, Agata Dziedzic, (...), Jan Komorowski, Bożena Kamińska, Bartek Wilczyński: Mapping chromatin accessibility and active regulatory elements reveals pathological mechanisms in human gliomas, in: Nature Communications, 2021, Vol. 12 (1), pp. 3621:1-17
  2. Paweł Krupa, Agnieszka S Karczyńska, Magdalena Mozolewska, Adam Liwo, Cezary Czaplewski: UNRES-Dock—protein–protein and peptide–protein docking by coarse-grained replica-exchange MD simulations, in: Bioinformatics, 2021, 37 (11), pp. 1613–1615
  3. Esther Rheinbay, Morten Muhlig Nielsen, (...), Jan Komorowski, (...). Gad Getz: Analyses of non-coding somatic drivers in 2,658 cancer whole genomes, in: Nature, 2020, Vol. 578 (7793), pp. 102-111
  4. Michał J. Dąbrowski, Bartosz Wojtas: Global DNA Methylation Patterns in Human Gliomas and Their Interplay with Other Epigenetic Modifications, in: International Journal of Molecular Sciences, 2019, Vol. 20 (14), pp. 1-17
  5. Michał Dramiński, Jacek Koronacki: rmcfs: An R Package for Monte Carlo Feature Selection and Interdependency Discovery, in: Journal of Statistical Software, 2018, Vol. 85 (12), pp. 1-28
  6. Michał J. Dąbrowski, Michał Dramiński, Klev Diamanti, Karolina Stępniak, Magdalena Mozolewska, Paweł Teisseyre, Jacek Koronacki, Jan Komorowski, Bożena Kamińska, Bartosz Wojtas: Unveiling new interdependencies between significant DNA methylation sites, gene expression profiles and glioma patients survival, in: Scientific Reports, 2018, Vol. 8 (1; Art. no 4390), pp. 1-12
  7. Husen M. Umer, Marco Cavalli, Michał J. Dąbrowski, Klev Diamanti, Marcin Kruczyk, Gang Pan, Jan Komorowski, Claes Wadelius: A Significant Regulatory Mutation Burden at a High-Affinity Position of the CTCF Motif in Gastrointestinal Cancers, in: Human Mutation, 2016, Vol. 9 (37), pp. 904-913
  8. Michał Dramiński, Michał J. Dąbrowski, Klev Diamanti, Jacek Koronacki, Jan Komorowski: Discovering Networks of Interdependent Features in High-Dimensional Problems, chapter in: Nathalie Japkowicz, Jerzy Stefanowski (eds.): Big Data Analysis: New Algorithms for a New Society, Springer International Publishing, Studies in Big Data, Vol. 16, 2016, ISBN: 978-3-319-26987-0, pp. 285-304
  9. Michał J. Dąbrowski, Susanne Bornelöv, Marcin Kruczyk, Nicholas Baltzer, Jan Komorowski: ‘True’ null allele detection in microsatellite loci: a comparison of methods, assessment of difficulties and survey of possible improvements, in: Molecular Ecology Resources, 2015, Vol. 15 (3), pp. 477-488
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