• Suche: Learning Functional Programming

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61

Practical problem-based programming learning using video
Tsukuta, Shigeo ; Yamaguchi, Takashi ; Kano, Tatsuya ; et al.
Artificial Life and Robotics. 24(3):422-429

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62

Using Visualization to Reduce the Cognitive Load of Threshold Concepts in Computer Programming
Winter, Victor ; Friend, Michelle ; Matthews, Michael ; et al.
2019 IEEE Frontiers in Education Conference (FIE) Frontiers in Education Conference (FIE), 2019 IEEE. :1-9 Oct, 2019

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63

Software visualization: The educational tool to enhance student learning
Maravic Cisar, S. ; Pinter, R. ; Radosav, D. ; et al.
The 33rd International Convention MIPRO MIPRO, 2010 Proceedings of the 33rd International Convention. :990-994 May, 2010

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64

Learning how to program
Upal, M.A. ; Padmanabhuni, S.
Engineering Solutions for the Next Millennium. 1999 IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.99TH8411) Electrical and computer engineering Electrical and Computer Engineering, 1999 IEEE Canadian Conference on. 2:1052-1056 vol.2 1999

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65

A strong complete schema for inductive functional logic programming
HERNANDEZ-ORALLO, J ; RAMIREZ-QUINTANA, M. J
ILP-99 : inductive logic programming (Bled, 24-27 June 1999)Lecture notes in computer science. :116-127

Computer science Informatique Sciences exactes et tech... Exact sciences and techn... Sciences appliquees Applied sciences …
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66

Quasi-online reinforcement learning for robots
Bakker, B. ; Zhumatiy, V. ; Gruener, G. ; et al.
Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006. Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on. :2997-3002 2006

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67

Supervised learning-aided optimization of expert-driven functional protein sequence annotation
SOINOV, Lev ; KANAPIN, Alexander ; KAPUSHESKY, Misha
Algorithms in bioinformatics (Bergen, 17-21 September 2004)Lecture notes in computer science. :159-169

Genetics Génétique Computer science Informatique Sciences exactes et tech... Exact sciences and techn... …
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68

A graph theoretical regression model for brain connectivity learning of Alzheimer'S disease
Hu, Chenhui ; Cheng, Lin ; Sepulcre, Jorge ; et al.
2013 IEEE 10th International Symposium on Biomedical Imaging Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on. :616-619 Apr, 2013

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69

Structured Multicategory Support Vector Machines with Analysis of Variance Decomposition
Lee, Yoonkyung ; Kim, Yuwon ; Lee, Sangjun ; et al.
Biometrika, 2006 Sep 01. 93(3), 555-571.

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70

Learning minimal covers of functional dependencies with queries
HERMO, M ; LAVIN, V
ALT'99 : algorithmic learning theory (Tokyo, 6-8 December 1999)Lecture notes in computer science. :291-300

Computer science Informatique Mathematics Mathématiques Sciences exactes et tech... Exact sciences and techn... …
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71

Learning programming using program visualization techniques
Baldwin, L.P. ; Kuljis, J.
Proceedings of the 34th Annual Hawaii International Conference on System Sciences System sciences System Sciences, 2001. Proceedings of the 34th Annual Hawaii International Conference on. :8 pp. 2001

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72

A minimax method for learning functional networks
CASTILLO, E ; GUTIERREZ, J. M ; COBO, A ; et al.
Neural processing letters. 11(1):39-49

Computer science Informatique Sciences exactes et tech... Exact sciences and techn... Sciences appliquees Applied sciences …
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73

From Zero to Python in 10.5 Hours: Building Foundational Programming Skills with Marine Biology Graduate Students and Researchers in an Introductory Workshop Series.
Timms, Geoffrey P. ; Guyon, Jeffrey R.
Science & Technology Libraries. 2023, Vol. 42 Issue 3, p371-390. 20p.

Marine biology Biology students Graduate students Python programming langu... Scientific visualization Active learning
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74

Stochastic programming model based on synthesizing effect function
Lei Zhou ; Fa-Chao Li
2009 International Conference on Machine Learning and Cybernetics Machine Learning and Cybernetics, 2009 International Conference on. 5:2675-2679 Jul, 2009

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76

Structure verification of deep neural networks at compilation time
Piñeyro, Leonardo ; Pardo, Alberto ; Viera, Marcos
In Journal of Computer Languages December 2021 67

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77

MiSaSiM: A resource-aware programming environment for computer systems engineering education
Wills, Linda ; Wills, Scott
2007 37th Annual Frontiers In Education Conference - Global Engineering: Knowledge Without Borders, Opportunities Without Passports Frontiers In Education Conference - Global Engineering: Knowledge Without Borders, Opportunities Without Passports, 2007. FIE '07. 37th Annual. :S1C-7-S1C-12 Oct, 2007

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78

PROPUESTA METODOLÓGICA PARA DESARROLLAR UN PROGRAMA CON PROGRAMACIÓN ESTRUCTURADA A PARTIR DEL PARADIGMA FUNCIONAL.
Trejos Buriticá, Omar Iván
Ciencia e Ingenieria Neogranadina. dic2013, Vol. 23 Issue 2, p137-156. 20p.

Computer programming Structured programming Learning Computer software Computer science
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79

A Multi-Objective Programming Approach to Compromising Classification Performance Metrics
Yaman, Sibel ; Lee, Chin-Hui
2007 IEEE Workshop on Machine Learning for Signal Processing Machine Learning for Signal Processing, 2007 IEEE Workshop on. :87-92 Aug, 2007

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80

One step up the abstraction ladder : Combining algebras : From functional pieces to a whole
FRANK, A. U
Spatial information theory : cognitive and computational foundations of geographic information science (Stade, 25-29 August 1999)Lecture notes in computer science. :95-107

Geology Géologie Computer science Informatique Telecommunications Télécommunications …
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