REPRESENTATIVE PAPERS:


DEPARTMENT OF THEORETICAL FOUNDATIONS OF COMPUTER SCIENCE

THEORY OF DISTRIBUTED AND COMPUTING SYSTEMS

1.M. Knapik, A. Męski, W. Penczek. Action Synthesis for Branching Time Logic: Theory and Applications. ACM Transactions on Embedded Computing Systems (TECS). TECS vol.  14 ,  2015 ,Article No. 64
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2. A. Avron, B. Konikowska, A. Zamansky. Efficient reasoning with inconsistent information using C-systems. Information Sciences, vol.  296, 2015,  pp. 219–236
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3. I. De Falco, E. Laskowski, R. Olejnik, U. Scafuri, E. Tarantino, M. Tudruj. Parallel extremal optimization in processor load balancing for distributed applications. Applied Soft Computing , vol.  46,  2016,   pp.  187–203
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4. M. Tudruj, J. Borkowski, D. Kopański, E. Laskowski, Ł. Maśko, A. Smyk. PEGASUS DA framework for distributed program execution control based on application global states monitoring. Concurrency and Computation: Practice and Experience. Special Issue: Combined Special Issues on Intelligent e-Services and PPAM 2013.  vol.  27,  2015 , pp. 1027–1053
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5. A. Męski, W. Penczek, G. Rozenberg. Model checking temporal properties of reaction systems. Information Sciences, vol .  313, 2015,  pp.  22–42
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6. A. Męski, W. Penczek, M. Szreter, B. Woźna-Szcześniak, A. Zbrzezny. BDD-versus SAT-based bounded model checking for the existential fragment of linear temporal logic with knowledge: algorithms and their performance. Autonomous Agents and Multi-Agent Systems , vol.  28, 2014,  pp 558–604
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7. S. Ambroszkiewicz, J. Brzeziński, W. Cellary, A. Grzech, K. Zieliński. Advanced SOA Tools and Applications. Studies in Computational Intelligence  vol.  499,  2014,
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8. V. Goranko, W. Jamroga. State and path coalition effectivity models of concurrent multi-player games. Autonomous Agents and Multi-Agent Systems, vol. 30,  2016,  pp.  446–485
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9. W. Drabent. Correctness and Completeness of Logic Programs. Journal ACM Transactions on Computational Logic. TOCL  vol.  17, 2016 , Article No. 18
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CRYPTOGRAPHY

1.P. Morawiecki, J. Pieprzyk, M. Srebrny, M. Straus. Cube Attacks and Cube-Attack-Like Cryptanalysis on the Round-Reduced Keccak Sponge Function. Advances in Cryptology -- EUROCRYPT 2015 - Lecture Notes in Computer Science , vol. 9056, pp.  733-761
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2.P. Morawiecki, M. Srebrny. A SAT-based preimage analysis of reduced Keccak hash functions. Information Processing Letters. Vol.  113, pp.  392-397.
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3. P. Morawiecki, K. Gaj, E. Homsirikamol, K. Matusiewicz, J. Pieprzyk, M. Rogawski, M. Srebrny, M. Wójcik. ICEPOLE: High-Speed, Hardware-Oriented Authenticated Encryption. Cryptographic Hardware and Embedded Systems – CHES 2014,  Lecture Notes in Computer Science , vol. 8731, pp.  392-413.
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DEPARTMENT OF ARTIFICIAL INTELLIGENCE

FOUNDATIONS OF ARTIFICIAL INTELLIGENCE

1. K. Makowski, G. Gielerak, E. Kramarz, S.T. Wierzchoń, G. Kamiński, J. Kowal, P. Krzesiński, A. Zegadło, A. Skrobowski. Left ventricular diastolic dysfunction is associated with impaired baroreflex at rest and during orthostatic stress in hypertensive patients with left ventricular hypertrophy. Journal of Human Hypertension,  vol. 27, pp. 2013:465-73
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2. M. Lucińska, S.T. Wierzchoń: Spectral Clustering Based on Analysis of Eigenvector Properties. In: K. Saeed and M. Snasel, eds. Computer Information Systems and Industrial Management - 13th IFIP TC8 International Conference, CISIM 2014, Lecture Notes in Computer Science  8838,  pp. 43-54,
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3. S.T. Wierzchoń, M.A. Kłopotek: Algorytmy analizy skupień. Wydawnictwo Naukowo-Techniczne, Warszawa, 2015, ISBN: 978-83-7926-261-8
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4. D. Czerski,  K. CiesielskiM. DramińskiM. KłopotekP. ŁozińskiS. Wierzchoń: What NEKST? - semantic search engine for Polish Internet. IN: Guy De Tre and Przemysław Grzegorzewski and Janusz Kacprzyk and Jan W. Owsiński and Wojciech Penczek and Sławomir Zadrożny, (eds), Challenging problems and solutions in intelligent systems, Studies in Computational Intelligence, 2016, pp. 335-347.
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5. S. Chojnacki, M. Kłopotek: Latency of Neighbourhood Based Recommender Systems. Fundamenta Informaticae vol. 139, 2015,  pp. 229-248
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6. P. Borkowski, K. Ciesielski, M. A. Kłopotek: Unsupervised aggregation of categories for document labelling. LNAI 8502, Proc. ISMIS2014, Methodologies for Intelligent Systems, 2015, pp. 335-344.
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7. M. Kłopotek: What is the value of information - search engine point of view. Lecture Notes in Computer Science  8104, 2013, pp.1-12
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8. S.Metzger, R.Schenkel, M.SydowAspect-based Similar Entity Search in Semantic Knowledge Graphs with Diversity-awareness and Relaxation. Proceedings of the IEEE/WIC/ACM WI-IAT 2014, pp. 60-69, ISBN 978-1-4799-4143-8, DOI 10.1109/WI-IAT.2014.17, IEEE, 2014 
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9. M.Sydow, M.Pikuła, R.Schenkel. The Notion of Diversity in Graphical Entity Summarisation on Semantic Knowledge Graphs. Journal of Intelligent Information Systems, vol.  41,  2013, pp. 109-149,60-69
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10. M.Sydow. Approximation Guarantees for Max Sum and Max Min Facility Dispersion with Parameterised Triangle Inequality and Applications in Result Diversification. Mathematica Applicanda vol. 42,  2014,  pp. 241-257
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LINGUISTIC ENGINEERING

1. A. Przepiórkowski, J. Hajič, E. Hajnicz, Z. Urešová. Phraseology in two Slavic valency dictionaries: Limitations and perspectives. International Journal of Lexicography, 29, 2016.
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2. M. Ogrodniczuk, K. Głowińska, M. Kopeć, A. Savary, M. Zawisławska. Coreference in Polish: Annotation, Resolution and Evaluation. Walter De Gruyter, 2015.
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3. A. Wawer. Towards Domain-Independent Opinion Target Extraction. 2015 IEEE International Conference on Data Mining Workshops (ICDMW), 2015,  pp. 1326–1331
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4. A. Patejuk, A. Przepiórkowski. Parallel development of linguistic resources: Towards a structure bank of Polish. Prace Filologiczne, LXV, 2015, pp. 255–270,
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5. W. Gruszczyński, M. Ogrodniczuk (eds.). Jasnopis, czyli mierzenie zrozumiałości polskich tekstów użytkowych. Wydawnictwo ASPRA-JR, Warszawa, 2015.
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6. M. Marciniak, A. Mykowiecka. Nested term recognition driven by word connection strength. Terminology  vol. 21, 2015, pp. 189-204
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7. M. MarciniakA. Mykowiecka. Terminology extraction from medical texts in Polish. Journal of Biomedical Semantics,vol. 5, 2014.
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8. A. Wróblewska, A. Przepiórkowski. Towards a weighted induction method of dependency annotation. [w:] Adam Przepiórkowski, Maciej Ogrodniczuk (eds.) Advances in Natural Language Processing: Proceedings of the 9th International Conference on NLP, PolTAL 2014. Lecture Notes in Artificial Intelligence 8686 , 2014, pp. 164–176
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9. M. Woliński. Morfeusz reloaded. In: N. Calzolari, K. Choukri, T. Declerck, H. Loftsson, B. Maegaard, J. Mariani, A. Moreno, J. Odijk, S. Piperidis (eds.) Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014), 2014, pp.  1106–1111
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10. Ł. Kobyliński. PoliTa: A multitagger for Polish. [w:] N. Calzolari, K. Choukri, T. Declerck, H. Loftsson, B. Maegaard, J. Mariani, A. Moreno, J. Odijk, S. Piperidis (eds.) Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014), 2014,  pp. 2949–2954
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STATISTICAL ANALYSIS AND MODELLING

1. Ł. Dębowski. Hilberg Exponents: New Measures of Long Memory in the Process. IEEE Transactions on Information Theory, vol. 61,  2015,  pp. 5716-5726.
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2. Ł. Dębowski. Maximal Repetitions in Written Texts: Finite Energy Hypothesis vs. Strong Hilberg Conjecture. Entropy  vol. 17, 2015, pp. 5903-5919
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3. S. Jaroszewicz, M. Korzeń. PaCAL: A Python Package for Arithmetic Computations with Random Variables. Journal of Statistical Software, vol. 57,  2014
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4. J. Mielniczuk, P. Teisseyre. Using random subspace method for prediction and variable importance assessment in linear regression. Computational Statistics and Data Analysis , vol. 71, 2014, pp. 725–742.
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5. S. Matwin, A. Pesaranghader, M. Sokolova, R.G. Beiko. Data and text mining simDEF: definition-based semantic similarity measure of gene ontology terms for functional similarity analysis of genes. Bioinformatics,  vol. 32, 2016, pp. 1380–1387.
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6. P. Pokarowski, J. Mielniczuk. Combined l1 and Greedy l0 Penalized Least Squares for Linear Model Selection. Journal of Machine Learning Research  vol. 16 , 2015, pp. 961-992.
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7. M. Sołtysł, S. Jaroszewicz, P. Rzepakowski. Ensemble methods for uplift modeling. Data Mining and Knowledge Discovery vol. 29, 2015, 1531–1559.
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8. E. N de Souza, K. Boerder, S. Matwin, B. Worm. Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning. PLOS 2015, vol. 10.
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COMPUTATIONAL BIOLOGY

1. H. M. Umer, M. Cavalli, M. J. Dabrowski, K. Diamanti, M. Kruczyk, G. Pan, J. Komorowski*, C. Wadelius*, A significant regulatory mutation burden at a high affinity position of the CTCF motif in gastrointestinal cancers, Human Mutation, to appear.
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2. W. Weigl, A. Bieryło, M. Wielgus, Ś. Krzemień-Wiczyńska, I. Szymusik, M. Kołacz and M. J. Dąbrowski (accepted). Analgesic efficacy of intrathecal fentanyl during the period of the highest analgesic demand after caesarean section: A randomised controlled study, Medicine, to appear.
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3. M. Dramiński, M.J. Dąbrowski, K. Diamanti, J. Koronacki, J. Komorowski: Discovering Networks of Interdependent Features in High-Dimensional Problems. In: Big Data Analysis: New Algorithms for a New Society, N. Japkowicz i J. Stefanowski (eds.), Studies in Computational Intelligence 2016,  pp. 285-304.
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4. E. Nowakowska, J. Koronacki, S. Lipovetsky: Dimensionality reduction for data of unknown cluster structure, Information Sciences,  vol. 330, 2016, pp. 74–87.
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5. M. Dramiński: ADX Algorithm for Supervised Classification, Challenges in Computational Statistics and Data Mining, S. Matwin i J. Mielniczuk (eds.), Studies in Computational Intelligence  2016,  pp.39-52.
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6. M.J. Dąbrowski, S. Bornelöv, M. Kruczyk, N. Baltzer and J. Komorowski (2015). Truenull allele detection in microsatellite loci: a comparison of methods. Assessment of difficulties and survey of possible improvements. Molecular Ecology Resources, vol. 15, 2015, pp. 477-488.
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7. Z. Khaliq, M. Leijon, S. Belák and J. Komorowski (2015). A complete map of potential pathogenicity markers of avian influenza virus subtype H5 predicted from 11 expressed proteins. BMC Microbiology vol. 15, 2015
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8. E. Nowakowska, J. Koronacki, S. Lipovetsky: Clusterability assessment for Gaussian mixture models. Applied Mathematics and Computation, vol 256, . 2015 , 591-601
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Archive of publications (2000 - 2015)

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