Literatura académica sobre el tema "Frugal learning"
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Artículos de revistas sobre el tema "Frugal learning"
Qu, Xiaoyu, Xutian Qin y Xiaopeng Wang. "Construction of Frugal Innovation Path in the Context of Digital Transformation: A Study Based on NCA and QCA". Sustainability 15, n.º 3 (23 de enero de 2023): 2158. http://dx.doi.org/10.3390/su15032158.
Texto completoOkano, Marcelo T., Henry de Castro Lobo dos Santos, Edson Luiz Ursini, Marcelo Eloy Fernandes y Jaqueline Geisa Cunha Gomes. "Open and Distance Learning (ODL) : Traditional or Frugal Innovation?" Contemporary Economics 17, n.º 1 (31 de marzo de 2023): 24–42. http://dx.doi.org/10.5709/ce.1897-9254.497.
Texto completoWu, Qingyun, Chi Wang y Silu Huang. "Frugal Optimization for Cost-related Hyperparameters". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 12 (18 de mayo de 2021): 10347–54. http://dx.doi.org/10.1609/aaai.v35i12.17239.
Texto completoSánchez Sánchez, Carlos Raúl, Jacqueline Boysselle y Sebastiano A. Delre. "“Learning by doing” como detonador de un comportamiento innovador y frugal de alumnos en prácticas". Recherches en Sciences de Gestion N° 156, n.º 3 (27 de julio de 2023): 309–40. http://dx.doi.org/10.3917/resg.156.0309.
Texto completoNayak, Nancy, Vishnu Raj y Sheetal Kalyani. "Leveraging Online Learning for CSS in Frugal IoT Network". IEEE Transactions on Cognitive Communications and Networking 6, n.º 4 (diciembre de 2020): 1350–64. http://dx.doi.org/10.1109/tccn.2020.2985354.
Texto completoPizzi, R. "Learning from lions: frugal surgical innovation in the wild". Bulletin of the Royal College of Surgeons of England 105, n.º 1 (enero de 2023): 14–17. http://dx.doi.org/10.1308/rcsbull.2023.8.
Texto completoKwan, Wei Ling, Magiswary Dorasamy, Abdul Aziz Bin Ahmad, Jayamalathi Jayabalan, Pradeep Kumar y Lingeswaran Subermaniam. "Digital taxation to promote frugal innovation in institutions of higher learning: a three-decade systematic literature review". F1000Research 10 (18 de octubre de 2021): 1055. http://dx.doi.org/10.12688/f1000research.73318.1.
Texto completoKwan, Wei Ling, Magiswary Dorasamy, Abdul Aziz Bin Ahmad, Jayamalathi Jayabalan, Pradeep Kumar y Lingeswaran Subermaniam. "Digital taxation to promote frugal innovation in institutions of higher learning: a three-decade systematic literature review". F1000Research 10 (22 de marzo de 2022): 1055. http://dx.doi.org/10.12688/f1000research.73318.2.
Texto completoKartawinata, Budi Rustandi, Aldi Akbar, Aditya Wardhana y Khansa Fairuz Citra. "Influence of Financial Literacy and Frugal Lifestyle on the Concept of Childfree in Childbearing Age Couples (PUS) in West Java". Journal of Business Management and Economic Development 2, n.º 02 (1 de marzo de 2024): 589–601. http://dx.doi.org/10.59653/jbmed.v2i02.653.
Texto completoBalcan, Maria-Florina, Tuomas Sandholm y Ellen Vitercik. "Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 3227–34. http://dx.doi.org/10.1609/aaai.v34i04.5721.
Texto completoTesis sobre el tema "Frugal learning"
Santos, Leandro Lima dos. "Bricolagem e inovatividade organizacional como antecedentes da inovação frugal em mercados emergentes". Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/12/12139/tde-07022019-160810/.
Texto completoInnovation has been broadly recognized as a fundamental source of competitive advantage for organizations. This study sought to highlight, through the perspective of the organizational learning theory, that companies need to be able to recombine and create their resources through the bricolage behavior in order to develop the frugal innovation in emerging markets. Thus, in this research we tried to answer the following question: Is bricolage an antecedent of frugal innovation for companies in emerging markets? Therefore, in this work the main objective was to identify whether bricolage can influence the development of frugal innovation. In addition, it was also analyzed whether bricolage is stimulated in crisis contexts, evidenced in emerging markets due to resource scarcity and financial crises, as in the case of Brazil. In this sense, the following hypotheses were established: H1: The bricolage process is positively related to frugal innovation; H2: Organizational innovativeness positively moderates the relationship between bricolage and frugal innovation; H3: A crisis context encourages the use of bricolage in companies to develop resources. These hypotheses were statistically tested using the structural equation modeling technique, using a database collected by the survey method encompassing 215 companies in Brazil. The results allowed to support the hypothesis H1 and H3 confirming, respectively, the positive influence of bricolage in the development of frugal innovation, and the influence of the crisis context on the bricolage behavior. The hypothesis H2 was not confirmed, denoting that organizational innovativeness does not necessarily moderate the relationship between bricolage and frugal innovation. This study has contributed to the literature of bricolage and frugal innovation, as well as established a connection between both, evidencing the bricolage as antecedent to develop frugal innovation, especially in contexts of crisis in emerging markets such as experienced in Brazil
Deschamps, Sébastien. "Apprentissage actif profond pour la reconnaissance visuelle à partir de peu d’exemples". Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS199.
Texto completoAutomatic image analysis has improved the exploitation of image sensors, with data coming from different sensors such as phone cameras, surveillance cameras, satellite imagers or even drones. Deep learning achieves excellent results in image analysis applications where large amounts of annotated data are available, but learning a new image classifier from scratch is a difficult task. Most image classification methods are supervised, requiring annotations, which is a significant investment. Different frugal learning solutions (with few annotated examples) exist, including transfer learning, active learning, semi-supervised learning or meta-learning. The goal of this thesis is to study these frugal learning solutions for visual recognition tasks, namely image classification and change detection in satellite images. The classifier is trained iteratively by starting with only a few annotated samples, and asking the user to annotate as little data as possible to obtain satisfactory performance. Deep active learning was initially studied with other methods and suited our operational problem the most, so we chose this solution. In this thesis, we have developed an interactive approach, where we ask the most informative questions about the relevance of the data to an oracle (annotator). Based on its answers, a decision function is iteratively updated. We model the probability that the samples are relevant, by minimizing an objective function capturing the representativeness, diversity and ambiguity of the data. Data with high probability are then selected for annotation. We have improved this approach, using reinforcement learning to dynamically and accurately weight the importance of representativeness, diversity and ambiguity of the data in each active learning cycle. Finally, our last approach consists of a display model that selects the most representative and diverse virtual examples, which adversely challenge the learned model, in order to obtain a highly discriminative model in subsequent iterations of active learning. The good results obtained against the different baselines and the state of the art in the tasks of satellite image change detection and image classification have demonstrated the relevance of the proposed frugal learning models, and have led to various publications (Sahbi et al. 2021; Deschamps and Sahbi 2022b; Deschamps and Sahbi 2022a; Sahbi and Deschamps2022)
Tuo, Aboubacar. "Extraction d'événements à partir de peu d'exemples par méta-apprentissage". Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG098.
Texto completoInformation Extraction (IE) is a research field with the objective of automatically identifying and extracting structured information within a given domain from unstructured or minimally structured text data. The implementation of such extractions often requires significant human efforts, either in the form of rule development or the creation of annotated data for systems based on machine learning. One of the current challenges in information extraction is to develop methods that minimize the costs and development time of these systems whenever possible. This thesis focuses on few-shot event extraction through a meta-learning approach that aims to train IE models from only few data. We have redefined the task of event extraction from this perspective, aiming to develop systems capable of quickly adapting to new contexts with a small volume of training data. First, we propose methods to enhance event trigger detection by developing more robust representations for this task. Then, we tackle the specific challenge raised by the "NULL" class (absence of events) within this framework. Finally, we evaluate the effectiveness of our proposals within the broader context of event extraction by extending their application to the extraction of event arguments
Pereira, Maria N?bia Gomes de Lucena. "Avalia??o da aprendizagem no Curso T?cnico em Agroind?stria, no IFCE- Campus Iguatu, atrav?s do desenvolvimento de atividades em um projeto de pesquisa com umbu-caj?" Universidade Federal Rural do Rio de Janeiro, 2010. https://tede.ufrrj.br/jspui/handle/jspui/2350.
Texto completoMade available in DSpace on 2018-08-20T13:21:14Z (GMT). No. of bitstreams: 1 2010 - Maria Nubia Gomes de Lucena Pereira.pdf: 3051812 bytes, checksum: 81841ffaf806c12662c2ec81c36821cc (MD5) Previous issue date: 2010-10-08
This work has analyzed the contribution of the development of activities of a research project applied in the teaching-learning process, hoping that the students of the Technical Course in Agroindustry of the Federal Institute of Education, Science and Technology ? Campus Iguatu, in the class of fruits and vegetables processing as active agents, comprehend and solidify their knowledge. In that sense, students of the Technical Course in Agroindustry produced teaching materials that could be used for the capacity of the producers of Vila Cajazeiras, with formulation techniques that could assemble value to the fruit of umbucaj? (Spondias sp). To evaluate the pedagogical process, two groups of 16 students have been created. The first group consisted of students from the Technical Course in Agroindustry with the curriculum in the integrated course (test group) and the second, students from the Technical Course in Agroindustry with the curriculum in the modulated course (control group). These students had already taken the class of fruits and vegetables processing the semester before. The evaluation method used was to evaluate the attitude of the individual, building a questionnaire about the umbu-caj? fruit with affirmatives referent to the necessary concepts and knowledge to comprehend these steps. This instrument has been applied in three different steps. For the control group, the instrument has been applied only once. In the extension activity, 16 people from the community have participated. The students were evaluated by the producers that participated in the extension activity. The processed product, nectar of umbu-caj?, has been evaluated referencing the physical-chemical, sensorial and microbiological parameters. In the physical-chemical determinations, the current legislation has been used to compare the results. In the sensorial evaluations, accepting tests have been used. As for the teaching-learning process, it has been observed that the test scores for each subject have been gradually rising as the learning would materialize, reaching the final test with more homogeneous answers. The medium scores were 4,8; 5,2 and 6,9 for T1, T2 and T3, respectively. As the students were being inserted in the context of the contemplated units of the class, it has been noted that the developed activities contributed to elevate their knowledge. In the control group the learning level was lower than in the test group. The results of the second group (control group) indicate that the students of the first group (test group) obtained higher comprehension of the proposed activities in this project, making this student search for interdisciplinary, produce his own learning, establish non-traditional pedagogical relations and learn new methods to assimilate new information and processing technologies of the umbu-caj? fruit, to better support its proposed work. Therefore, this work was important to link the student to the researching world, making him an active agent of all the process, assigning him with responsibility and making it possible for him to create different ways of constructing his own knowledge.
O presente trabalho analisou a contribui??o do desenvolvimento de atividades de um projeto de pesquisa aplicado no processo de ensino-aprendizagem, esperando-se que os estudantes do Curso T?cnico em Agroind?stria do Instituto Federal de Educa??o, Ci?ncia e Tecnologia - Campus Iguatu, da disciplina de processamento de frutos e hortali?as, como agentes ativos, compreendessem e solidificassem o conhecimento. Nesse sentido, estudantes do Curso T?cnico em agroind?stria produziram o material did?tico que pudesse ser utilizado para a capacita??o dos produtores da Vila Cajazeiras, com t?cnicas de formula??es para que eles pudessem agregar valor ao fruto do umbu-caj? (Spondias sp). Para avaliar o processo pedag?gico, foram constitu?dos dois grupos de 16 estudantes, sendo o primeiro do Curso T?cnico em Agroind?stria da matriz curricular do Curso integrado (Grupo Teste) e o segundo, por alunos do Curso T?cnico em Agroind?stria da matriz curricular do curso modulado (Grupo Controle). Esses alunos j? haviam cursado a disciplina de processamento de frutos e hortali?as no semestre anterior. Utilizou-se o m?todo de avalia??o de atitude do indiv?duo construindo-se question?rio relativo ao fruto do umbu-caj? com afirmativas referentes aos conceitos e conhecimentos necess?rios para compreender estas etapas. Esse instrumento foi aplicado em tr?s etapas diferentes. Para o Grupo controle, o instrumento foi aplicado apenas uma vez. Na atividade de extens?o participaram 16 pessoas da comunidade. Os alunos foram avaliados pelos produtores que participaram da atividade de extens?o. O produto processado, n?ctar de umbu-caj?, foi avaliado em rela??o aos par?metros f?sico-qu?micos, sensoriais e microbiol?gicos. Nas determina??es f?sico-qu?micas, para comparar os resultados, utilizou-se a legisla??o vigente. Nas avalia??es sensoriais, utilizaram-se testes de aceita??o. Quanto ao processo de ensino-aprendizagem, verificou-se que a m?dia para cada sujeito foi aumentando gradativamente nos testes, ? medida que a aprendizagem se concretizava, chegando ao ?ltimo teste com uma maior homogeneidade nas respostas, cujas m?dias foram 4,8; 5,2 e 6,9 para T1, T2 e T3, respectivamente. Na medida em que os alunos foram sendo inseridos no contexto das unidades contempladas na disciplina, verificou-se que as atividades desenvolvidas contribu?ram para elevar seu n?vel de conhecimento. O Grupo Controle o n?vel de aprendizagem foi menor do que no grupo teste. Os resultados obtidos no segundo grupo (grupo controle) indicaram que os estudantes do primeiro grupo (grupo teste) obtiveram melhor compreens?o das atividades propostas neste projeto, proporcionando a esse aluno buscar a interdisciplinaridade, produzir seus pr?prios conhecimentos, estabelecer rela??es pedag?gicas n?o-tradicionais e aprender outro m?todo para assimilar novos conhecimentos e tecnologias de processamento do fruto de umbu-caj?, para melhor fundamentar a sua proposta de trabalho. Portanto, o trabalho foi importante para vincular o estudante ao mundo da pesquisa, fazendo-o um agente ativo de todo o processo, atribuindo-lhe responsabilidade e possibilitando-lhe um modo diferente de construir seu pr?prio conhecimento.
Libros sobre el tema "Frugal learning"
Allee, Judith Waite y Melissa L. Morgan. Educational Travel on a Shoestring: Frugal Family Fun and Learning Away from Home. Shaw, 2002.
Buscar texto completoCapítulos de libros sobre el tema "Frugal learning"
Ackers, Helen Louise, James Ackers-Johnson, John Chatwin y Natasha Tyler. "International Mobility and Learning in the UK National Health Service". En Healthcare, Frugal Innovation, and Professional Voluntarism, 1–11. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48366-5_1.
Texto completoGrossetête, Loïc, Alexandre Marois, Bénédicte Chatelais, Christian Gagné y Daniel Lafond. "Active Learning for Capturing Human Decision Policies in a Data Frugal Context". En Machine Learning, Optimization, and Data Science, 395–407. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95470-3_30.
Texto completoDoddamani, Shridhar T. y Arunkumar C. Giriyapur. "Project Based Learning in Laboratories Using Open Source Technologies: Case Study of a Frugal Approach". En Proceedings of the International Conference on Transformations in Engineering Education, 525–33. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1931-6_60.
Texto completoShepherd, Dean A., Vinit Parida y Joakim Wincent. "Making Do with the Resources at Hand to Improve One’s Life and Others’ Lives". En Entrepreneurial Responses to Chronic Adversity, 1–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04884-5_1.
Texto completoBhatti, Yasser, Shaista E. Khilji y Radha Basu. "Frugal innovation". En Globalization, Change and Learning in South Asia, 123–45. Elsevier, 2013. http://dx.doi.org/10.1016/b978-0-85709-464-3.50007-6.
Texto completoWatson, Elizabeth. "Free or Externally Funded Professional Development for Frugal Librarians". En Advances in Library and Information Science, 90–106. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4675-9.ch007.
Texto completoWatson, Elizabeth. "Free or Externally Funded Professional Development for Frugal Librarians". En Open Source Technology, 292–307. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-7230-7.ch017.
Texto completoPrakash, Ujwal. "Hallmark of Robustness in Frugal Management Techniques". En Key Factors and Use Cases of Servant Leadership Driving Organizational Performance, 293–312. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-8820-8.ch012.
Texto completoHai-Jew, Shalin. "Using a SoTL Framework and Disciplinary Context to Sketch Teaching and Learning Research". En Building and Maintaining Adult Learning Advantage, 65–105. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-4516-4.ch004.
Texto completoDhayal, Karambir Singh, Mohsen Brahmi, Shruti Agrawal, Luigi Aldieri y Concetto Paolo Vinci. "A Paradigm Shift in Education Systems Due to COVID-19". En Frugal Innovation and Social Transitions in the Digital Era, 157–66. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-5417-6.ch015.
Texto completoActas de conferencias sobre el tema "Frugal learning"
Deschamps, Sebastien y Hichem Sahbi. "Reinforcement-based Display Selection for Frugal Learning". En 2022 26th International Conference on Pattern Recognition (ICPR). IEEE, 2022. http://dx.doi.org/10.1109/icpr56361.2022.9956544.
Texto completoSahbi, Hichem, Sebastien Deschamps y Andrei Stoian. "Frugal Learning for Interactive Satellite Image Change Detection". En IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021. http://dx.doi.org/10.1109/igarss47720.2021.9553385.
Texto completoTu, Huy y Tim Menzies. "FRUGAL: Unlocking Semi-Supervised Learning for Software Analytics". En 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 2021. http://dx.doi.org/10.1109/ase51524.2021.9678617.
Texto completoMartignon, Laura, Ulrich Hoffrage, Jan Woike, Tim Erickson y Joachim Engel. "Fast-and-frugal trees for decision-making". En Decision Making Based on Data. International Association for Statistical Education, 2019. http://dx.doi.org/10.52041/srap.19307.
Texto completoMallibhat, Kaushik, M. Vijayalakshmi, Madhu Asundi y Shivaprasad Channangi. "FRUGAL PROTOTYPING: AN INTERVENTION TO IMPROVE PROTOTYPING SKILLS IN ENGINEERING EDUCATION". En 14th International Conference on Education and New Learning Technologies. IATED, 2022. http://dx.doi.org/10.21125/edulearn.2022.0644.
Texto completoDeschamps, Sebastien y Hichem Sahbi. "Reinforcement-Based Frugal Learning for Interactive Satellite Image Change Detection". En IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2022. http://dx.doi.org/10.1109/igarss46834.2022.9883633.
Texto completoMarois, Alexandre, Loic Grossetete, Benedicte Chatelais y Daniel Lafond. "Evaluation of Evolutionary Algorithms Under Frugal Learning Constraints for Online Policy Capturing". En 2021 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA). IEEE, 2021. http://dx.doi.org/10.1109/cogsima51574.2021.9475930.
Texto completoGosavi, Gita y Gaur Sunder. "Rapidly Deployable and Frugal Blended Learning Platform for Re-skilling and Up-skilling Needs". En COMPUTE 2022: COMPUTE 2022. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3561833.3564857.
Texto completoJain, Varun, Ramakrishna Perla y Ramya Hebbalaguppe. "[POSTER] AirGestAR: Leveraging Deep Learning for Complex Hand Gestural Interaction with Frugal AR Devices". En 2017 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct). IEEE, 2017. http://dx.doi.org/10.1109/ismar-adjunct.2017.76.
Texto completo"Using Frugal Education Principles and the RPG Maker MV Game Engine to Aid the Co-creation of Digital Game-based Learning Resources". En 13th EuropeanConference on Game Based Learning. ACI, 2020. http://dx.doi.org/10.34190/gbl.20.029.
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