Relevant bibliographies by topics / Frugal learning

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Frugal learning'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Frugal learning"

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Qu, Xiaoyu, Xutian Qin, and Xiaopeng Wang. "Construction of Frugal Innovation Path in the Context of Digital Transformation: A Study Based on NCA and QCA." Sustainability 15, no. 3 (2023): 2158. http://dx.doi.org/10.3390/su15032158.

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With the continuous advancement of digital globalization, enterprises need to seek development opportunities in the context of diversification and resource shortage. Frugal innovation provides a new way for enterprises to realize social value and create a win-win situation. Based on 113 enterprises’ survey data, fuzzy set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) are used to explore the multiple concurrency factors and causality mechanisms of digital transformation, organizational resilience, learning from failure and design thinking for frugal innovation.
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Okano, Marcelo T., Henry de Castro Lobo dos Santos, Edson Luiz Ursini, Marcelo Eloy Fernandes, and Jaqueline Geisa Cunha Gomes. "Open and Distance Learning (ODL) : Traditional or Frugal Innovation?" Contemporary Economics 17, no. 1 (2023): 24–42. http://dx.doi.org/10.5709/ce.1897-9254.497.

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New information and communication technologies (ICTs) are contributing to the advancement and popularization of distance learning, and its use by educational institutions is accelerating. Some characteristics of distance learning are remarkable, such as its quantity, scalability, ability to serve many students at the same time, scope, lower costs, and so on. Some of these characteristics refer to a type of innovation called frugal, which is the ability to "do better with fewer resources for more people", that is, create significantly more value and minimize the use of resources. The objective
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Astuti, Retno Widi, Henry Praherdhiono, and Dedi Kuswandi. "Pengembangan Teknik Pembelajaran dengan Prinsip Frugal Education." JKTP: Jurnal Kajian Teknologi Pendidikan 7, no. 3 (2024): 129. http://dx.doi.org/10.17977/um038v7i32024p129.

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The development of learning techniques using the principles of frugal education is carried out to produce practical, easy, cheap, interesting and valid learning in accordance with the principles of frugal education or frugal education. The development was carried out to overcome problems in learning using games, namely difficulties in providing games to be used in learning, and the use of technology available in schools was not optimal. The development of this learning technique uses the Plomp model. Plomp is a learning development model that is considered simple, flexible and flexible because
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Wu, Qingyun, Chi Wang, and Silu Huang. "Frugal Optimization for Cost-related Hyperparameters." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 12 (2021): 10347–54. http://dx.doi.org/10.1609/aaai.v35i12.17239.

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The increasing demand for democratizing machine learning algorithms calls for hyperparameter optimization (HPO) solutions at low cost. Many machine learning algorithms have hyperparameters which can cause a large variation in the training cost. But this effect is largely ignored in existing HPO methods, which are incapable to properly control cost during the optimization process. To address this problem, we develop a new cost-frugal HPO solution. The core of our solution is a simple but new randomized direct-search method, for which we provide theoretical guarantees on the convergence rate and
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Sánchez Sánchez, Carlos Raúl, Jacqueline Boysselle, and 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, no. 3 (2023): 309–40. http://dx.doi.org/10.3917/resg.156.0309.

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Les entreprises ont besoin d’employés capables de répondre aux nouveaux défis dans les domaines commerciaux, sociaux et environnementaux. Cette étude analyse l’impact de certaines méthodes innovantes d’apprentissage. Avec un échantillon de 462 étudiants et un design casi-expérimental avec pré et post-test et un groupe de control, notre étude combine le comportement au travail innovant (CTI) avec les principes de l’innovation frugale (PIF) pour obtenir le comportement au travail innovant et frugal (CTIF). Les résultats révèlent que les étudiants de troisième cycle en alternance présentent un CT
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Albert, Martin. "Teaching Sustainable Frugal Innovation Development to Business Students." International Journal of Management and Applied Research 10, no. 2 (2023): 314–38. https://doi.org/10.18646/2056.102.23-024.

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Frugal innovations have the potential to address social, ecological, and economic issues. Students as future engineers and managers can play an important role to foster frugal innovations. Previous research related to the teaching of frugal innovation in higher education focus primarily on engineering and design study courses. There are no publications how to teach the concept of frugal innovation to future managers respectively, to students of the economic/business sciences. I introduce and evaluate a new concept for teaching sustainable frugal innovation to business students by means of LEGO
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Nayak, Nancy, Vishnu Raj, and Sheetal Kalyani. "Leveraging Online Learning for CSS in Frugal IoT Network." IEEE Transactions on Cognitive Communications and Networking 6, no. 4 (2020): 1350–64. http://dx.doi.org/10.1109/tccn.2020.2985354.

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Pizzi, R. "Learning from lions: frugal surgical innovation in the wild." Bulletin of the Royal College of Surgeons of England 105, no. 1 (2023): 14–17. http://dx.doi.org/10.1308/rcsbull.2023.8.

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Fresh from his inspiring talk at the Future Surgery show, Romain Pizzi tells us about coming up with unique solutions on a shoestring to treat his wildlife patients. Can surgeons learn a thing or two?
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Kwan, Wei Ling, Magiswary Dorasamy, Abdul Aziz Bin Ahmad, Jayamalathi Jayabalan, Pradeep Kumar, and Lingeswaran Subermaniam. "Digital taxation to promote frugal innovation in institutions of higher learning: a three-decade systematic literature review." F1000Research 10 (October 18, 2021): 1055. http://dx.doi.org/10.12688/f1000research.73318.1.

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Background: In the era of the Fourth Industrial Revolution (IR 4.0), digital taxation emerged as a tool for accelerating the economic growth of a nation. While Industry 4.0 focuses on enabling real-time decision-making with sophisticated technology to enhance productivity, digital taxation can serve as an important tool for improving business sustainability. Institutions of higher learning (IHL), which aim to design an IR 4.0 educational ecosystem, can embrace digital taxation, as they face various challenges with different resources. The literature indicates that frugal innovation through dig
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Kwan, Wei Ling, Magiswary Dorasamy, Abdul Aziz Bin Ahmad, Jayamalathi Jayabalan, Pradeep Kumar, and Lingeswaran Subermaniam. "Digital taxation to promote frugal innovation in institutions of higher learning: a three-decade systematic literature review." F1000Research 10 (March 22, 2022): 1055. http://dx.doi.org/10.12688/f1000research.73318.2.

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Background: In the era of the Fourth Industrial Revolution (IR 4.0), digital taxation emerged as a tool for accelerating the economic growth of a nation. While Industry 4.0 focuses on enabling real-time decision-making with sophisticated technology to enhance productivity, digital taxation can serve as an important tool for improving business sustainability. Institutions of higher learning (IHL), which aim to design an IR 4.0 educational ecosystem, can embrace digital taxation, as they face various challenges with different resources. The literature indicates that frugal innovation through dig
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Dissertations / Theses on the topic "Frugal learning"

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Leconte, Louis. "Compression and federated learning : an approach to frugal machine learning." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS107.

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Les appareils et outils “intelligents” deviennent progressivement la norme, la mise en œuvre d'algorithmes basés sur des réseaux neuronaux artificiels se développant largement. Les réseaux neuronaux sont des modèles non linéaires d'apprentissage automatique avec de nombreux paramètres qui manipulent des objets de haute dimension et obtiennent des performances de pointe dans divers domaines, tels que la reconnaissance d'images, la reconnaissance vocale, le traitement du langage naturel et les systèmes de recommandation.Toutefois, l'entraînement d'un réseau neuronal sur un appareil à faible capa
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Cazorla, Clément. "Analyse d'images en microscopie par réseaux de neurones dans un contexte frugal." Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSES028.

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Dans ce manuscrit de thèse, nous explorons l'usage de réseaux de neurones dans un contexte frugal, c'est-à-dire avec peu de données d'entraînement, appliqué à des tâches d'analyse d'images de microscopie. Au cours de ces travaux, j'ai fourni un travail substantiel d'intégration dans des interfaces utilisateur ergonomiques. Celles-ci prennent la forme de plugins Napari, un logiciel open-source de visualisation d'images multi-dimensionnelles. Plus largement, ce travail permet de rapprocher les utilisateurs de microscopes et les technologies d'apprentissage profond, actuellement complexes à appré
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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/.

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A inovação tem sido amplamente reconhecida como uma fonte essencial de vantagem competitiva para as organizações. Este estudo buscou evidenciar, sob a ótica da teoria da aprendizagem organizacional, que as empresas precisam ser capazes de recombinar e criar seus recursos por meio do comportamento de bricolagem, com a finalidade de desenvolver a inovação frugal em mercados emergentes. Assim, nesta pesquisa procurou-se responder a seguinte pergunta: A bricolagem configura-se como um antecedente da inovação frugal para empresas em mercados emergentes? Logo, neste trabalho o objetivo principal foi
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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.

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L’analyse automatique d’images a permis d’améliorer l’exploitation des capteurs d’image, avec des données qui proviennent de différents capteurs tels que des caméras de téléphone, des caméras de surveillance, des imageurs satellites ou encore des drones. L’apprentissage profond obtient d’excellents résultats dans les applications d’analyse d’images où de grandes quantités de données annotées sont disponibles, mais apprendre un nouveau classifieur d’images à partir de zéro est une tâche difficile. La plupart des méthodes de classification d’images sont supervisées, nécessitant des annotations,
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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.

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L'extraction d'information est un champ de recherche dont l'objectif est d'identifier et extraire automatiquement des informations structurées, dans un domaine donné, à partir de données textuelles pas ou peu structurées. La mise en œuvre de telles extractions demande souvent des moyens humains importants pour l'élaboration de règles d'extraction ou encore pour la constitution de données annotées pour les systèmes utilisant de l'apprentissage automatique. Un des défis actuels dans le domaine de l'extraction d'information est donc de développer des méthodes permettant de réduire, dans la mesure
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Kara, Sandra. "Unsupervised object discovery in images and video data." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG019.

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Cette thèse explore les méthodes d'apprentissage auto-supervisé pour la localisation d'objets, communément appelées « Object Discovery ». La localisation d'objets dans les images et les vidéos est un élément essentiel des tâches de vision par ordinateur telles que la détection, la ré-identification, le suivi, etc. Les algorithmes supervisés actuels peuvent localiser (et classifier) les objets avec précision, mais ils sont coûteux en raison de la nécessité de données annotées. Le processus d'étiquetage est généralement répété pour chaque nouvelle donnée ou catégorie d'intérêt, limitant ainsi le
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Cherdo, Yann. "Détection d'anomalie non supervisée sur les séries temporelle à faible coût énergétique utilisant les SNNs." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4018.

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Dans le cadre de la maintenance prédictive du constructeur automobile Renault, cette thèse vise à fournir des solutions à faible coût énergétique pour la détection non supervisée d'anomalies sur des séries temporelles. Avec l'évolution récente de l'automobile, de plus en plus de données sont produites et doivent être traitées par des algorithmes d'apprentissage automatique. Ce traitement peut être effectué dans le cloud ou directement à bord de la voiture. Dans un tel cas, la bande passante du réseau, les coûts des services cloud, la gestion de la confidentialité des données et la perte de don
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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.

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Submitted by Sandra Pereira (srpereira@ufrrj.br) on 2018-08-20T13:21:14Z No. of bitstreams: 1 2010 - Maria Nubia Gomes de Lucena Pereira.pdf: 3051812 bytes, checksum: 81841ffaf806c12662c2ec81c36821cc (MD5)<br>Made 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<br>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
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Books on the topic "Frugal learning"

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Garstka, Cruz. Frugal Life : Learning to Live on Minimum Wage Painlessly: Frugal Housewifes Manuel. Independently Published, 2021.

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Allee, Judith Waite, and Melissa L. Morgan. Educational Travel on a Shoestring: Frugal Family Fun and Learning Away from Home. Shaw, 2002.

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Book chapters on the topic "Frugal learning"

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Peixoto, Eduardo, Diogo Torres, Davide Carneiro, Bruno Silva, and Paulo Novais. "Efficient MLOps: Meta-learning Meets Frugal AI." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-86489-6_26.

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Abstract The advent of large Machine Learning models and the steep increase in the demand for AI solutions occurs at the same point in time in which policies are being enacted to implement more sustainable processes in virtually every sector. This means there is a need for more, better and larger models, which require significant computational resources, while at the same time a call for a decrease in the energy spent in the processes associated to MLOps. In this paper we propose a reduced set of meta-features that can be used to characterize sets of data and their relationship with model perf
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Ackers, Helen Louise, James Ackers-Johnson, John Chatwin, and Natasha Tyler. "International Mobility and Learning in the UK National Health Service." In Healthcare, Frugal Innovation, and Professional Voluntarism. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48366-5_1.

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Grossetête, Loïc, Alexandre Marois, Bénédicte Chatelais, Christian Gagné, and Daniel Lafond. "Active Learning for Capturing Human Decision Policies in a Data Frugal Context." In Machine Learning, Optimization, and Data Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95470-3_30.

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Bellinger, Colin, Isaac Tamblyn, and Mark Crowley. "Learning When to Observe: A Frugal Reinforcement Learning Framework for a High-Cost World." In Communications in Computer and Information Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-74640-6_18.

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Doddamani, Shridhar T., and Arunkumar C. Giriyapur. "Project Based Learning in Laboratories Using Open Source Technologies: Case Study of a Frugal Approach." In Proceedings of the International Conference on Transformations in Engineering Education. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1931-6_60.

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Lopiano, Gloria, Andrea Campagner, Cristina Cereda, Stephana Carelli, and Federico Cabitza. "Explainable Machine Learning for Neonatal Screening: A Fast&Frugal Decision Tree for Rare Metabolic Disease Detection." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-95838-0_25.

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Shepherd, Dean A., Vinit Parida, and Joakim Wincent. "Making Do with the Resources at Hand to Improve One’s Life and Others’ Lives." In Entrepreneurial Responses to Chronic Adversity. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04884-5_1.

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AbstractThis chapter—“Making Do with the Resources at Hand to Improve One’s Life and Others’ Lives”—highlights the bright side of entrepreneurial action in response to chronic adversity. In this chapter, we discuss how most prior research has emphasized the importance of slack resources to explain creativity, innovation, and entrepreneurship. However, scholars have tended to under-emphasize the role of necessity in generating innovations and to over-emphasize the firm level of analysis when investigating value creation and capture. To add more balance to this discussion, in this chapter, we de
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Bhatti, Yasser, Shaista E. Khilji, and Radha Basu. "Frugal innovation." In Globalization, Change and Learning in South Asia. Elsevier, 2013. http://dx.doi.org/10.1016/b978-0-85709-464-3.50007-6.

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Nyagadza, Brighton, Abu Bashar, Neo Ligaraba, et al. "Artificial Intelligence (AI), Machine Learning (ML) and Big Data Analytics' Impact on Frugal Digital Marketing Firms." In Disruptive Frugal Digital Innovation in Africa. Emerald Publishing Limited, 2025. https://doi.org/10.1108/978-1-83549-568-120251012.

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Watson, Elizabeth. "Free or Externally Funded Professional Development for Frugal Librarians." In Advances in Library and Information Science. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4675-9.ch007.

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Librarians need professional development opportunities even during difficult economic times with limited library budgets. Fortunately, creative and frugal librarians are finding external funding for professional development, and benefiting from free or low-cost professional development tools and opportunities. Many of these frugal solutions are online. Social media, bookmarking services, e-learning platforms like WebJunction and Lyrasis, listservs, and webinars are all explored as such online solutions. Conference scholarships, interdepartmental cooperation, and community partnerships are also
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Conference papers on the topic "Frugal learning"

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Kahenga, Ferdinand, Antoine Bagula, and Sajal K. Das. "FedDAFL: Federated Transfer Learning with Domain Adaptation for Frugally Labeled Datasets." In GLOBECOM 2024 - 2024 IEEE Global Communications Conference. IEEE, 2024. https://doi.org/10.1109/globecom52923.2024.10901238.

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Deschamps, Sebastien, and Hichem Sahbi. "Reinforcement-based Display Selection for Frugal Learning." In 2022 26th International Conference on Pattern Recognition (ICPR). IEEE, 2022. http://dx.doi.org/10.1109/icpr56361.2022.9956544.

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Sahbi, Hichem, Sebastien Deschamps, and Andrei Stoian. "Frugal Learning for Interactive Satellite Image Change Detection." In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021. http://dx.doi.org/10.1109/igarss47720.2021.9553385.

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Tu, Huy, and Tim Menzies. "FRUGAL: Unlocking Semi-Supervised Learning for Software Analytics." In 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 2021. http://dx.doi.org/10.1109/ase51524.2021.9678617.

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Martignon, Laura, Ulrich Hoffrage, Jan Woike, Tim Erickson, and Joachim Engel. "Fast-and-frugal trees for decision-making." In Decision Making Based on Data. International Association for Statistical Education, 2019. http://dx.doi.org/10.52041/srap.19307.

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Fast-and-frugal trees for classification/decision are at the intersection of three families of models: lexicographic, linear and tree-based. We briefly examine the classification performance of simple models when making inferences out of sample, in 11 medical data sets in terms of Receiver Operating Characteristics diagrams and predictive accuracy. The heuristic approaches, Naïve Bayes and fast- and-frugal trees, outperform models that are normatively optimal when fitting data. The success of fast-and-frugal trees lies in their ecological rationality: their construction exploits the structure
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Mallibhat, Kaushik, M. Vijayalakshmi, Madhu Asundi, and Shivaprasad Channangi. "FRUGAL PROTOTYPING: AN INTERVENTION TO IMPROVE PROTOTYPING SKILLS IN ENGINEERING EDUCATION." In 14th International Conference on Education and New Learning Technologies. IATED, 2022. http://dx.doi.org/10.21125/edulearn.2022.0644.

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Deschamps, Sebastien, and Hichem Sahbi. "Reinforcement-Based Frugal Learning for Interactive Satellite Image Change Detection." In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2022. http://dx.doi.org/10.1109/igarss46834.2022.9883633.

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Marois, Alexandre, Loic Grossetete, Benedicte Chatelais, and Daniel Lafond. "Evaluation of Evolutionary Algorithms Under Frugal Learning Constraints for Online Policy Capturing." In 2021 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA). IEEE, 2021. http://dx.doi.org/10.1109/cogsima51574.2021.9475930.

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Gosavi, Gita, and Gaur Sunder. "Rapidly Deployable and Frugal Blended Learning Platform for Re-skilling and Up-skilling Needs." In COMPUTE 2022: COMPUTE 2022. ACM, 2022. http://dx.doi.org/10.1145/3561833.3564857.

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Jain, Varun, Ramakrishna Perla, and Ramya Hebbalaguppe. "[POSTER] AirGestAR: Leveraging Deep Learning for Complex Hand Gestural Interaction with Frugal AR Devices." In 2017 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct). IEEE, 2017. http://dx.doi.org/10.1109/ismar-adjunct.2017.76.

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Reports on the topic "Frugal learning"

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Shuzo Kato, Shuzo Kato. A Frugal Monitor for Invasive Crayfish integrating Underwater Imaging and Machine Learning Classification. Experiment, 2024. http://dx.doi.org/10.18258/67102.

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