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Interactive Learning of Data Structures and Algorithmic Schemes [chapter]

Clara Segura, Isabel Pita, Rafael del Vado Vírseda, Ana Isabel Saiz, Pablo Soler
2008 Lecture Notes in Computer Science  
We present an interactive environment called Vedya for the visualization of data structures and algorithmic schemes which can be used as a very useful educational tool in Computer Science.  ...  By means of the Vedya tool, the students benefited from complementary and interactive material, facilitating the intuitive comprehension of most typical operations of classical data structures without  ...  Introduction We present an interactive environment tool called Vedya for the visualization of data structures and algorithmic schemes.  ... 
doi:10.1007/978-3-540-69384-0_85 fatcat:cobxlv24czf27aypzu7wn4afx4

Locally non-negative linear structure learning for interactive image retrieval

Lei Bao, Juan Cao, Tian Xia, Yong-Dong Zhang, Jintao Li
2009 Proceedings of the seventeen ACM international conference on Multimedia - MM '09  
structure, this algorithm preserves the non-negative inherent characteristic of image data and can truly reveal the intrinsic structure of the images corpus, especially the asymmetric relationship between  ...  It has two main merits: first, it is robust to the small sample learning problem since it learns structure from both labeled and unlabeled data; second, by emphasizing the non-negativity of locally linear  ...  and active learning algorithm.  ... 
doi:10.1145/1631272.1631355 dblp:conf/mm/BaoCXZL09 fatcat:q2dbyqxwazcytlqlynfgl4dh6q

miSTAR: miRNA target prediction through modeling quantitative and qualitative miRNA binding site information in a stacked model structure

Gert Van Peer, Ayla De Paepe, Michiel Stock, Jasper Anckaert, Pieter-Jan Volders, Jo Vandesompele, Bernard De Baets, Willem Waegeman
2016 Nucleic Acids Research  
Single model structures insufficiently cope with this complex training data structure, consisting of feature vectors of unequal length as a consequence of the varying number of miRNA binding sites in different  ...  Using logistic regression and random forests, we applied the stacked model approach to a unique data set of 7990 probed miRNA-mRNA interactions, hereby including the largest number of miRNAs in model training  ...  and the Flemish Government (department EWI).  ... 
doi:10.1093/nar/gkw1260 pmid:27986855 pmcid:PMC5397177 fatcat:cxav2rw4anh4hikokfrcgd2zcq

An Intelligent Tutoring System for Interactive Learning of Data Structures [chapter]

Rafael del Vado Vírseda, Pablo Fernández, Salvador Muñoz, Antonio Murillo
2009 Lecture Notes in Computer Science  
The high level of abstraction necessary to teach data structures and algorithmic schemes has been more than a hindrance to students.  ...  In the first place, we describe the tool called Vedya for the visualization of data structures and algorithmic schemes.  ...  The Vedya Tool Vedya is an integrated interactive environment for learning data structures and algorithmic schemes presented for the first time in [9] .  ... 
doi:10.1007/978-3-642-01973-9_7 fatcat:qlj4ymvclfewvl7irisdk223gu

A Neo-Piagetian Analysis of Algorithmic Thinking Development through the "Sorted" Digital Game

Suparat CHUECHOTE, Artorn NOKKAEW, Apichat PHONGSASITHORN, Parames LAOSINCHAI
2020 Contemporary Educational Technology  
game for self-learning of computing concepts.  ...  To later reflect on their operational reasoning and hence decision-making, the series of game actions were logged for individual empirical data.  ...  ACKNOWLEDGEMENT This research was partially supported by The Institute for the Promotion of Teaching Science and Technology (IPST) and the Thailand Research Fund (TRG5880196).  ... 
doi:10.30935/cet.685959 fatcat:argxw5zajfd4tdyyri6wmxqj6i

An intrinsically-motivated schema mechanism to model and simulate emergent cognition

Olivier L. Georgeon, Frank E. Ritter
2012 Cognitive Systems Research  
, and autonomous learning.  ...  Following these drives, the agent autonomously learns regularities afforded by the environment, and hierarchical sequences of behaviors adapted to these regularities.  ...  Support for this study was provided by ONR (N00014-06-1-0164 and N00014-08-1-0481), DTRA (HDTRA 1-09-1-0054), and ANR (ANR-10-PDOC-007-01).  ... 
doi:10.1016/j.cogsys.2011.07.003 fatcat:yjxw43j7yjc4hf5nbteufpytv4

Teaching Quality Evaluation and Scheme Prediction Model Based on Improved Decision Tree Algorithm

Sujuan Jia, Yajing Pang
2018 International Journal of Emerging Technologies in Learning (iJET)  
This paper proposes a decision tree model by taking the teaching quality data and the statistical analysis results of the learn-er's personalized behaviour as inputs.  ...  Finally, according to the actual statisti-cal data of one academic year, the teaching quality evaluation was effectively completed and the direction of future teaching prediction was proposed.  ...  Through research analysis and data sorting, the learning model of A student was randomly selected, and then the learning results of this student during the first semester was summarized by iterative scheme  ... 
doi:10.3991/ijet.v13i10.9460 fatcat:3ebeler7fjhfxc4kvghpmstgtm

bNEAT: a Bayesian network method for detecting epistatic interactions in genome-wide association studies

Bing Han, Xue-wen Chen
2011 BMC Genomics  
The merits of the proposed approach lie in two aspects: a suitable score for Bayesian network structure learning that can reflect higher-order epistatic interactions and a heuristic Bayesian network structure  ...  Detecting epistatic interactions plays a significant role in improving pathogenesis, prevention, diagnosis and treatment of complex human diseases.  ...  This article has been published as part of BMC Genomics Volume 12 Supplement 2, 2011: Selected articles from the IEEE International Conference  ... 
doi:10.1186/1471-2164-12-s2-s9 pmid:21989368 pmcid:PMC3194240 fatcat:mi33c5czyjasxmam35jv7htpte

Building meta-learning algorithms basing on search controlled by machine complexity

Norbert Jankowski, Krzysztof Grabczewski
2008 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)  
Metalearning algorithm presented in this paper is universal and may be applied to any type of CI problems.  ...  The learning algorithm is augmented by meta-knowledge repository which accumulates information about progress of the search through the space of candidate solutions.  ...  and their interaction, etc.  ... 
doi:10.1109/ijcnn.2008.4634313 dblp:conf/ijcnn/JankowskiG08 fatcat:dhb57dfu3ngy5bbli457ddpxs4

Adaptivity in Agent-Based Routing for Data Networks [article]

David H. Wolpert, Sergey Kirshner, Chris J. Merz, Kagan Tumer
1999 arXiv   pre-print
Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems (MAS's) in noisy environments.  ...  One important way to have the interaction structure connecting agents itself be adaptive is to have the intentions and/or actions of the agents be in the input spaces of the other agents, much as in Stackelberg  ...  Acknowledgements The authors would like to thank Jeremy Frank, Joe Sill, Ann Bell and Marjory Johnson for helpful discussion.  ... 
arXiv:cs/9912011v1 fatcat:c7w7racwqnfydevxvwzrcs4tqi

On case-based learnability of languages

Christoph Globig, Klaus P. Jantke, Steffen Lange, Yasubumi Sakakibara
1997 New generation computing  
The present algorithm meets this goal by a combination of a competitive Hebbian learning scheme and a self-organizing map algorithm.  ...  For their construction using an unsupervised learning algorithm the templates need to be structurally adaptive.  ...  Acknowledgement: One of the authors (RD) gratefully acknowledges the hospitality of RIKEN (Tokyo) he received during a visit in February 1996.  ... 
doi:10.1007/bf03037560 fatcat:xgubcvsxerdunm7f7uxeviznvm

Eureka!: A Tool for Interactive Knowledge Discovery [chapter]

Giuseppe Manco, Clara Pizzuti, Domenico Talia
2002 Lecture Notes in Computer Science  
The tool combines a visual clustering method, to hypothesize meaningful structures in the data, and a classification machine learning algorithm, to validate the hypothesized structures.  ...  In this paper we describe an interactive, visual knowledge discovery tool for analyzing numerical data sets.  ...  , that combines a visual clustering method, to hypothesize meaningful structures in the data, and a classification machine learning algorithm, to validate the hypothesized structures.  ... 
doi:10.1007/3-540-46146-9_38 fatcat:ubsuhrn7qfghvga4kwbscygzvy

Reusability and adaptability of interactive resources in Web-based educational systems

Abdulmotaleb El Saddik, Stephan Fischer, Ralf Steinmetz
2001 Journal on Educational Resources in Computing  
The teacher can both adjust the level of explanation and the level of interactivity of an animation, and hence influence the presentation and the results of the algorithms being illustrated (program reusability  ...  In this article, we discuss the reusability and adaptability aspects of interactive multimedia content in web-based learning systems.  ...  ACKNOWLEDGMENTS The authors thank the Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (BMBF) and the Volkswagen Stiftung, which partially funded the research project.  ... 
doi:10.1145/376697.376699 fatcat:4ouajlkh3rbpnjldxtm6hzjhlm

Cooperative Learning for Distributed In-Network Traffic Classification

S.B. Joseph, H.R. Loo, I. Ismail, T. Andromeda, M.N. Marsono
2016 Proceeding of the Electrical Engineering Computer Science and Informatics  
In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification.  ...  Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote  ...  Acknowledgment This work is supported in part by CREST grant (UTM Vote No. 4B176) and Universiti Teknologi Malaysia Grant matching (UTM Vote No. 00M75)  ... 
doi:10.11591/eecsi.v3i1.1144 fatcat:xaa2oacxbngcbj57btln6hqjmq

Cooperative Learning for Distributed In-Network Traffic Classification

S.B. Joseph, H.R. Loo, I. Ismail, T. Andromeda, M.N. Marsono
2017 IOP Conference Series: Materials Science and Engineering  
In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification.  ...  Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote  ...  Acknowledgment This work is supported in part by CREST grant (UTM Vote No. 4B176) and Universiti Teknologi Malaysia Grant matching (UTM Vote No. 00M75)  ... 
doi:10.1088/1757-899x/190/1/012010 fatcat:3xwtkp55q5fwve2podtwq4po2e
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