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Generalizable and interpretable learning for configuration extrapolation
2021
Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
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To incorporate prior knowledge, the proposed tools (1) start from known configurations, (2) iteratively construct a new linear model, (3) extrapolate better performance configurations from that model, ...
We enhance this property with a graphical representation of how they arrived at the highest performance configuration. ...
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies. ...
doi:10.1145/3468264.3468603
fatcat:kfo5bmezwnbmtoinpnv2n5mbki
Collaborative learning model of infrastructure construction: a capability perspective
2015
Construction Innovation
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This Standard Model is extended to derive a novel Circular Model of dynamic learning capability that shows a new feedback loop between performance and learning. ...
Model of dynamic learning capability. ...
The learning system is socially complex due to the tacit nature of much knowledge. As a result, organisation members have incomplete knowledge of the learning system. ...
doi:10.1108/ci-05-2014-0031
fatcat:m2zlabqrrvcbtbhd4vg4qujysm
GVIS: A Facility for Adaptively Mashing Up and Representing Open Learner Models
[chapter]
2010
Lecture Notes in Computer Science
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The system is highly configurable: data sources, data aggregations, and visualizations can be configured on the fly without changing any part of the software and have an adaptive behavior based on user's ...
We explored this approach in the context of Life Long Learning, where different platforms or services are often used to support the learning process. ...
One of the most important components of adaptive learning systems is the student model, which is in charge of keeping track of the student's knowledge and skills acquired during the learning process. ...
doi:10.1007/978-3-642-16020-2_53
fatcat:f5braq5dwrf4ngtw6winw7h3gm
Ontologic Design of Software Engineering Knowledge Area Knowledge Components
2020
Advances in Science, Technology and Engineering Systems
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The design process of disciplines knowledge content degree programs and individual learning guidelines is connected with specifying the knowledge content frame, the configuration of which is defined with ...
in the form of knowledge expressions and knowledge components, and secondly, secure the knowledge components semantic interoperability withing the frame of their usage in educational environment and systems ...
Acknowledgment The work has been executed with the support of the Ministry of education and science of the Republic of Kazakhstan, grant № AP05134973. ...
doi:10.25046/aj050404
fatcat:nm25nf5rh5csrlwkvpiwycedmu
BoGraph: Structured Bayesian Optimization From Logs for Systems with High-dimensional Parameter Space
[article]
2021
arXiv
pre-print
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BoAnon provides an API enabling experts to encode knowledge of the system as performance models or components dependency. ...
However, the complexity of building probabilistic models has hindered its wider adoption. We propose BoAnon, a SBO framework that learns the system structure from its logs. ...
Acknowledgements A special thanks to Mihai Bujanca, Thomas Vanderstichele, and Yomna El-Serafy for their comments that improved the readability of the paper. ...
arXiv:2112.08774v1
fatcat:gu2axmdfbrap7kgnktmyliln5e
Proposal for a Multiagent Architecture for Self-Organizing Systems (MA-SOS)
[chapter]
2008
Lecture Notes in Computer Science
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This work investigates the trade-off between individual and collective behavior, to dynamically satisfy the requirements of the system through self-organization of its activities and individual (agent) ...
For this purpose, it is considered that each agent varies its behavioral laws (behaviorswitching) dynamically, guided by its emotional state in a certain time instant. ...
point of view. ...
doi:10.1007/978-3-540-69304-8_45
fatcat:r3uwnnqprvdbbhkyqroxntpwwu
Contextual cuing as a form of nonconscious learning: Theoretical and empirical analysis in large and very large samples
2016
Psychonomic Bulletin & Review
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low in a model assuming a single memory source drives learning and awareness. ...
The data support the absence of a positive relationship between recognition and the cuing effect both at the participant and configuration level, the probability of which being a false negative is very ...
Acknowledgments Ben Colagiuri was a recipient of a University of New South Wales Vice-Chancellor's Postdoctoral Research Fellowship (RG104440-1) while conducting the first experiment in this report. ...
doi:10.3758/s13423-016-1063-0
pmid:27220995
fatcat:c7fwqeyryzdczb35stvcy7ti3e
GVIS: An Integrating Infrastructure for Adaptively Mashing up User Data from Different Sources
2010
2010 14th International Conference Information Visualisation
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We applied our infrastructure to a set of federated Learning Management Systems, retrieving information from different sources and creating some indicators of the learning activity. ...
The system is highly configurable and adaptive: data sources, data aggregations, and visualizations can be configured on the fly by the administrative user without changing any part of the software, and ...
The configuration of the dashboard can be personalized based on some parameters set at a system level. ...
doi:10.1109/iv.2010.19
dblp:conf/iv/MazzolaM10
fatcat:7lelm2fkqrcuvcgu2f72k7jpru
Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis
[article]
2017
arXiv
pre-print
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While this line of research is promising to learn more accurate models at a lower cost, it is unclear why and when transfer learning works for performance modeling. ...
Recently, transfer learning has been applied to reduce the effort of constructing performance models by transferring knowledge about performance behavior across environments. ...
Kaestner's work is also supported by NSF awards 1318808 and 1552944 and the Science of Security Lablet (H9823014C0140). ...
arXiv:1709.02280v1
fatcat:44hubsccozegrcgnmfscjzq7ba
Transfer Learning for Improving Model Predictions in Highly Configurable Software
[article]
2017
arXiv
pre-print
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Usually, we learn a black-box model based on real measurements to predict the performance of the system given a specific configuration. ...
We propose a different solution: Instead of taking the measurements from the real system, we learn the model using samples from other sources, such as simulators that approximate performance of the real ...
Kaestner's work is also supported by NSF awards 1318808 and 1552944 and the Science of Security Lablet (H9823014C0140). Siegmund's work is supported by the DFG under the contract SI 2171/2. ...
arXiv:1704.00234v2
fatcat:4rja3jewinfjrb2zvkxy6kegmq
Integration of Semantically Annotated Data by the KnoFuss Architecture
[chapter]
2008
Lecture Notes in Computer Science
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Most of the existing work on information integration in the Semantic Web concentrates on resolving schema-level problems. ...
This paper describes how these features are exploited in our architecture KnoFuss, designed to support data-level integration of semantic annotations. ...
Acknowledgements This work was funded by the X-Media project (www.x-media-project.org) sponsored by the European Commission as part of the Information Society Technologies (IST) programme under EC grant ...
doi:10.1007/978-3-540-87696-0_24
fatcat:tq4mnjwc4reuvcul6vxcwfshla
Learning about Ecological Systems by Constructing Qualitative Models with DynaLearn
2012
Interdisciplinary Journal of e-Skills and Lifelong Learning
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A qualitative model of a system is an abstraction that captures ordinal knowledge and predicts the set of qualitatively possible behaviours of the system, given a qualitative description of its structure ...
In summing up the results, it is clear that from the perspective of systems thinking, the modeling activity affected students' perception of systems making them able to represent it in a more dynamic and ...
In recent years, there is strong support for the idea that Learning by Modeling (LbM), namely learning by manipulating and/or constructing models of the systems under study, is a promising pedagogical ...
doi:10.28945/1734
fatcat:wzeftldtlba43okcw2tvpydmei
KGSecConfig: A Knowledge Graph Based Approach for Secured Container Orchestrator Configuration
[article]
2021
arXiv
pre-print
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Our solution leverages keyword and learning models to systematically capture, link, and correlate heterogeneous and multi-vendor configuration space in a unified structure for supporting automation of ...
For automating security configuration of CO, we propose a novel Knowledge Graph based Security Configuration, KGSecConfig, approach. ...
learning model for minimizing the effect of bias. ...
arXiv:2112.12595v1
fatcat:3ddw5irclrgxfooe3chpwzqfpi
Parameter Learning Algorithms for Continuous Model Improvement Using Operational Data
[chapter]
2017
Lecture Notes in Computer Science
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Acknowledgments This work is part of the project "Health Monitoring and Life-Long Capability Management for SELf-SUStaining Manufacturing Systems (SelSus)" which is funded by the Commission of the European ...
and wider system-level models integrating component-level models. ...
Next (3) , we report on a performance analysis of two levels of integration of the OOBN model into the SelSus architecture using Online EM and fractional updating for parameter learning. ...
doi:10.1007/978-3-319-61581-3_11
fatcat:op7no2zn3zhqlk7lavosi4esl4
Creating and Appropriating Value from Project Management Resource Assets Using an Integrated Systems Approach
2014
Procedia - Social and Behavioral Sciences
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A micro-practice approach was adopted to identify activity configurations that represent the inflection points of value creation and appropriation in an integrated project management system. ...
The aim of the research reported here is to identify and characterise relationships between learning processes, dynamic capabilities, knowledge management and project management resource assets. ...
Brusoni, S., Prencipe, A., Salter, A., 1998. Mapping and measuring innovation in project-based firms, CoPS Working Paper No. 46, SPRU, University of Sussex. ...
doi:10.1016/j.sbspro.2014.03.012
fatcat:gsfsfz6cpnagndnkdangqustdm
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