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Foundations of Computing and Decision Sciences
The Journal of Poznan University of Technology
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Implications of Pooling Strategies in Convolutional Neural Networks: A Deep Insight

References [1] Reddit, Machine Learning . Available: https://www.reddit.com/r/MachineLearning/comments/2lmo0l/ama_geoffrey_hinton/clyj4jv/ [2] Achille A., Soatto S., Information dropout: Learning optimal representations through noisy computation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 2897-2905. [3] Boureau Y.-L., Le Roux N., Bach F., Ponce J., LeCun Y., Ask the locals: multi-way local pooling for image recognition, in Computer Vision (ICCV), 2011 IEEE International Conference on , 2011, 2651-2658. [4

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A Batching Machine Model for Lot Scheduling on a Single Machine

and algorithms, Omega , 31 , 2003, 365–378. [9] Potts C.N., Kovalyov M.Y., Scheduling with batching: a review, European Journal of Operational Research , 120 , 2000, 228–249. [10] Potts C.N., Van Wassenhove L.N., Integrating scheduling with batching and lotsizing: A review of algorithms and complexity, Journal of the Operational Research Society , 43 , 1992, 395–406. [11] Webster S.T., Baker K.R., Scheduling groups of jobs on a single machine, Operations Research , 43 , 1995, 692–703.

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Bayesian-Based Methods for the Estimation of the Unknown Model’s Parameters in the Case of the Localization of the Atmospheric Contamination Source

References [1] Bernardo, J. M. & Smith, A. F. M., Bayesian Theory , Wiley, 1994. [2] Fujimoto, K., Nakabayashi S., Applying GMDH algorithm to extract rules from examples, Systems Analysis Modelling Simulation , 43 , 10, 2003. 1311-1319. [3] Gelman, A., J. Carlin, H. Stern, and D. Rubin, Bayesian Data Analysis , Chapman & Hall/CRC, 2003. [4] Gifford, F. A. Jr. Atmospheric dispersion calculation using generalized Gaussian Plum model, Nuclear Safety , 1960, 2(2):56-59, 67

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Modeling Biological Systems Using Crowdsourcing

., Küffner R., Vega N. M., Prill R. J., Camacho D. M., Allison K. R., Aderhold A., Bonneau R., Chen Y., et al. Wisdom of crowds for robust gene network inference. Nature methods, 9(8):796, 2012. [43] Mavandadi S., Feng S., Yu F., Dimitrov S., Yu R., and Ozcan A. Biogames: A platform for crowd-sourced biomedical image analysis and telediagnosis. Games for Health Journal, 1(5):373{376, 2012. PMID: 23724363. [44] Mesarovic M. Systems Theory and Biology. Springer Verlag, 1968. [45] Meyer P., Cokelaer T., Chandran D., Kim K. H

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EOQ Revisited with Sustainability Considerations

-classical era, International Journal of Production Economics , 133 , 1, 2011, 43- 53. [14] Chen X., Benjaafar S., Elomri A., The carbon-constrained EOQ, Operations Research Letters, 41 , 2, 2013, 172-179. [15] Manikas A., Godfrey M., Inducing green behavior in a manufacturer, Global Journal of Business Research , 4 , 2, 2010, 27-38. [16] Letmathe P., Balakrishnan, N., Environmental considerations on the optimal product mix, European Journal of Operational Research , 167 , 2005, 398-412. [17] Penkuhn T

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Towards a Process Calculus for Rest: Current State of the Art

., Stroiński, A.: ROsWeL Workflow Language: A Declarative, Resource-oriented Approach. New Generation Computing 30(2-3), 141-164 (2012) [10] Busi, N., Gorrieri, R., Guidi, C., Lucchi, R., Zavattaro, G.: Towards a formal framework for choreography. In: In Proc. of 3rd International Workshop on Dis- tributed and Mobile Collaboration (DMC 2005). IEEE Computer. pp. 107-112. Society Press (2005) [11] Busi, N., Gorrieri, R., Guidi, C., Lucchi, R., Zavattaro, G.: Choreography and orchestration conformance for system design. In: Coordination Models

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Two New Decomposition Algorithms for Training Bound-Constrained Support Vector Machines*

.J., Keerthi S., Sundararajan S., A dual coordinate descent method for large-scale linear SVM, Proceedings of the 25th international conference on Machine learning , ACM, 2008, 408-415. [9] Hsu C.W., Lin C.J., A simple decomposition method for support vector machines, Machine Learning , 46, 1-3, 2002, 291{314. [10] Joachims T., SVMlight, http://svmlight.joachims.org/. [11] Joachims T., Training linear SVMs in linear time, ACM SIGKDD International Conference On Knowledge Discovery and Data Mining , 2006, 217-226. [12] Joachims T., Finley T., Yu C.N., Cutting

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A survey of graph coloring - its types, methods and applications

References [1] Chappell G. Hal A. Kundgen A. Ramamurthi R. Albertson, M.O. Coloring with no 2-colored p4's. Electronic Journal of Combinatorics, 11(1), 2004. [2] McDiarmid C. Reed B. Alon, N. Acyclic coloring of graphs. Random Structures and Algorithms, 2(3):277_288, 1991. [3] Sudakov B. Zaks A. Alon, N. Acyclic edge colorings of graphs. J. Graph Theory, 37(3):157_167, 2001. [4] Zaks A. Alon, N. Algorithmic aspects of acyclic edge colorings. Algorithmica, 32(4):611_614, 2002

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A Survey on Identifying and Addressing Business Analysis Problems

-6. [3] Bobkowska A., Wyrzykowski K., A model for the activities of business analysts in public administration for the prevention of hidden requirements (in Polish: Model działania analityka biznesowego w administracji publicznej w celu przeciwdziałania ukrytym wymaganiom), Roczniki Kolegium Analiz Ekonomicznych/Szkoła Główna Handlowa, 42, 2016, 13-26. [4] Charette R.N., Why software fails, IEEE Spectrum 42, 9, 2005, 42-49. [5] Cheng B., Atlee J., Research directions in requirements engineering, In: Proc. of Future of Software

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