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Bartlomiej Sniezynski
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A comparison of native and cross-platform frameworks for mobile applications
P Nawrocki, K Wrona, M Marczak, B Sniezynski
Computer 54 (3), 18-27, 2021
402021
VM reservation plan adaptation using machine learning in cloud computing
B Sniezynski, P Nawrocki, M Wilk, M Jarzab, K Zielinski
Journal of Grid Computing 17, 797-812, 2019
312019
Adapting everyday manipulation skills to varied scenarios
P Gajewski, P Ferreira, G Bartels, C Wang, F Guerin, B Indurkhya, ...
2019 international conference on robotics and automation (ICRA), 1345-1351, 2019
292019
Adaptable mobile cloud computing environment with code transfer based on machine learning
P Nawrocki, B Sniezynski, H Slojewski
Pervasive and Mobile Computing 57, 49-63, 2019
262019
Adaptive service management in mobile cloud computing by means of supervised and reinforcement learning
P Nawrocki, B Sniezynski
Journal of Network and Systems Management 26 (1), 1-22, 2018
242018
The use of LPR (logic of plausible reasoning) to obtain information on innovative casting technologies
S Kluska-Nawarecka, B Śnieżyński, W Parada, M Lustofin, ...
Archives of Civil and Mechanical Engineering 14 (1), 25-31, 2014
212014
Learning agent for a service-oriented context-aware recommender system in heterogeneous environment
P Nawrocki, B Sniezynski
Computing and Informatics 35 (5), 1005-1026, 2016
192016
Neural network modelling studies of steam oxidised kinetic behaviour of advanced steels and Ni-based alloys at 800° C for 3000 h
T Dudziak, P Gajewski, B Śnieżyński, V Deodeshmukh, M Witkowska, ...
Corrosion Science 133, 94-111, 2018
172018
Adaptive resource planning for cloud-based services using machine learning
P Nawrocki, M Grzywacz, B Sniezynski
Journal of Parallel and Distributed Computing 152, 88-97, 2021
162021
Watch: Wasserstein change point detection for high-dimensional time series data
K Faber, R Corizzo, B Sniezynski, M Baron, N Japkowicz
2021 IEEE International Conference on Big Data (Big Data), 4450-4459, 2021
152021
Autonomous context-based service optimization in mobile cloud computing
P Nawrocki, B Sniezynski
Journal of Grid computing 15, 343-356, 2017
152017
Adaptive context-aware energy optimization for services on mobile devices with use of machine learning
P Nawrocki, B Sniezynski
Wireless Personal Communications 115 (3), 1839-1867, 2020
142020
Knowledge visualization using optimized general logic diagrams
B Śnieżyński, R Szymacha, RS Michalski
Intelligent Information Processing and Web Mining: Proceedings of the …, 2005
142005
Proof searching algorithm for the logic of plausible reasoning
B Śnieżyński
Intelligent Information Processing and Web Mining: Proceedings of the …, 2003
142003
A strategy learning model for autonomous agents based on classification
B SNIEZYNSKI
Int. J. Appl. Math. Comput. Sci 25 (3), 471-482, 2015
132015
Agent-based adaptation system for service-oriented architectures using supervised learning
B Śnieżyński
Procedia Computer Science 29, 1057-1067, 2014
132014
Agent strategy generation by rule induction
B Sniezynski
Computing and Informatics 32, 1055-1078, 2013
132013
Combining rule induction and reinforcement learning: An agent-based vehicle routing
B Śniezyński, W Wójcik, JD Gehrke, J Wojtusiak
2010 ninth international conference on machine learning and applications …, 2010
132010
Converting a Naive Bayes Model into a Set of Rules.
B Sniezynski
Intelligent Information Systems, 221-229, 2006
132006
Probabilistic label algebra for the logic of plausible reasoning
B Śnieżyński
Intelligent Information Systems 2002: Proceedings of the IIS’2002 Symposium …, 2002
122002
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Artigos 1–20