Academic literature on the topic 'Procedure learning'
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Journal articles on the topic "Procedure learning"
Zentall, Thomas R. "Social learning mechanisms." Interaction Studies 12, no. 2 (July 21, 2011): 233–61. http://dx.doi.org/10.1075/is.12.2.03zen.
Full textMendelson, Shahar. "An Unrestricted Learning Procedure." Journal of the ACM 66, no. 6 (December 6, 2019): 1–42. http://dx.doi.org/10.1145/3361699.
Full textTsaih, R. R. "The softening learning procedure." Mathematical and Computer Modelling 18, no. 8 (October 1993): 61–64. http://dx.doi.org/10.1016/0895-7177(93)90163-s.
Full textWang, Zizhuang. "Temporal-Related Convolutional-Restricted-Boltzmann-Machine Capable of Learning Relational Order via Reinforcement Learning Procedure." International Journal of Machine Learning and Computing 7, no. 1 (February 2017): 1–8. http://dx.doi.org/10.18178/ijmlc.2017.7.1.610.
Full textHill, Christine, Mohamad El Zein, Abhishek Agnihotri, Margo Dunlap, Angela Chang, Alison Agrawal, Sindhu Barola, et al. "Endoscopic sleeve gastroplasty: the learning curve." Endoscopy International Open 05, no. 09 (September 2017): E900—E904. http://dx.doi.org/10.1055/s-0043-115387.
Full textGülüstan, Filiz. "Learning curve of septoplasty procedure." Turkish Journal of Ear Nose and Throat 29, no. 4 (January 31, 2020): 166–71. http://dx.doi.org/10.5606/tr-ent.2019.65265.
Full textAmmon, Kurt. "A learning procedure for mathematics." Annals of Mathematics and Artificial Intelligence 8, no. 3-4 (September 1993): 407–23. http://dx.doi.org/10.1007/bf01530800.
Full textMlodinow, Leonard D., and Ion O. Stamatescu. "An evolutionary procedure for machine learning." International Journal of Computer & Information Sciences 14, no. 4 (August 1985): 201–19. http://dx.doi.org/10.1007/bf00997019.
Full textSahdan, Shafizza, Alias Masek, Noor Atikah Zainal Abidin, and Juliati Jusoh. "Preliminary Study: Self-Regulated Learning Procedure." MATEC Web of Conferences 150 (2018): 05008. http://dx.doi.org/10.1051/matecconf/201815005008.
Full textMeehan, Anita M. "A Procedure for Learning Students' Names." Teaching of Psychology 17, no. 2 (April 1990): 125–26. http://dx.doi.org/10.1207/s15328023top1702_16.
Full textDissertations / Theses on the topic "Procedure learning"
Koelker, Rachel Lee Ellis Janet. "Comparing a discriminative stimulus procedure to a pairing procedure conditioning neutral social stimuli to function as conditioned reinforcers /." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/ark:/67531/metadc12143.
Full textJossen, Quentin. "Unsupervised learning procedure for nonintrusive appliance load monitoring." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209369.
Full textenergy advice. The required functionalities must however be rapidly defined if they are expected to be integrated in the future massive roll out.
Nonintrusive appliance load monitoring aims to derive appliance-specific information from the aggregate electricity consumption. While techniques have been developed since the 80’s, those mainly address the identification of previously learned appliances, from a database. Building such a database is an intrusive and tedious process which should be avoided. Whereas most recent efforts have focused on unsupervised techniques to disambiguate energy consumption into individual appliances, they usually rely on prior information about measured appliances such as the number of appliances, the number of states in each appliance as well as the power they consume in each state. This information should ideally be learned from the data. This topic will be addressed in the present research.
This work will present a framework for unsupervised learning for nonintrusive appliance
load monitoring. It aims to discover information about appliances of a household solely from its aggregate consumption data, with neither prior information nor user intervention. The learning process can be segmented into five tasks: the detection of on/off switching, the extraction of individual load signatures, the identification of
recurrent signatures, the discovery of two-state electrical devices and, finally, the elaboration
of appliance models. The first four steps will be addressed in this paper.
The suite of algorithms proposed in this work allows to discover the set of two-states electrical loads from their aggregated consumption. This, along with the evaluation
of their operating sequences, is a prerequisite to learn appliance models from the data. Results show that loads consuming power down to some dozens of watts can be learned from the data. This should encourage future researchers to consider such an unsupervised learning.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
Sjöblom, Niklas. "Evolutionary algorithms in statistical learning : Automating the optimization procedure." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160118.
Full textScania har länge jobbat med statistik men har på senare år investerat i att bli ett mer datadrivet företag och använder nu data science i nästan alla avdelningar på företaget. De algoritmer som utvecklas av data scientists måste optimeras för att kunna utnyttjas till fullo och detta är traditionellt sett en manuell och tidskrävade process. Detta examensarbete utreder om och hur väl evolutionära algoritmer kan användas för att automatisera optimeringsprocessen. Utvärderingen gjordes genom att implementera och analysera fyra varianter avgenetiska algoritmer med olika grader av komplexitet och trimningsparameterar. Algoritmen som var målet för optimering var XGBoost, som är en gradient boosted trädbaserad modell. Denna applicerades på data som tidigare hade modellerats i entävling. Resultatet visar att evolutionära algoritmer är applicerbara i att hitta bra modellermen påvisar även hur fundamentalt det är att arbeta med databearbetning innan modellering.
Koelker, Rachel Lee. "Comparing a discriminative stimulus procedure to a pairing procedure: Conditioning neutral social stimuli to function as conditioned reinforcers." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc12143/.
Full textYetter, Georgette. "Acceptability of a student assistance team procedure to school staff." Diss., [Lincoln, Neb. : University of Nebraska-Lincoln], 2003. http://www.unl.edu/libr/Dissertations/2003/YetterDis.pdf.
Full textCampbell, Fiona. "Imitative and nonimitative social learning using a two object/two action procedure." Thesis, University College London (University of London), 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327045.
Full textMcManus, Jacqueline Law Faculty of Law UNSW. "Capacity-development at work: the contribution of workplace-based learning to tax administration." Awarded by:University of New South Wales. School of Law, 2007. http://handle.unsw.edu.au/1959.4/29565.
Full textMatoug, Mohamed Ibrahim. "Procedure-knowledge expectation (PKE) model : as an assessment tool for measuring bricklayer trainees' planning skill." Thesis, University of Salford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335464.
Full textWard, Lindsey L. "Exploring facets of classroom management to promote student learning routine, procedure, and teachers' belief systems /." Theological Research Exchange Network (TREN), 2007. http://www.tren.com/search.cfm?p088-0193.
Full textStaff, Donald Michael Hyten Cloyd. "Utilizing staff training methods for developing a mathetics error correction procedure in a university classroom." [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9735.
Full textBooks on the topic "Procedure learning"
Stempel, Jeffrey W. Learning civil procedure. St. Paul, MN: West, 2013.
Find full textDon, Stuart, ed. Learning Canadian criminal procedure. Toronto: Carswell, 1986.
Find full text1943-, Stuart Don, ed. Learning Canadian criminal procedure. 5th ed. Scarborough, Ont: Carswell, 1998.
Find full text1943-, Stuart Don, ed. Learning Canadian criminal procedure. 6th ed. Scarborough, Ont: Carswell, 2000.
Find full textDelisle, R. J. Learning Canadian criminal procedure. 4th ed. Scarborough, Ont: Carswell, 1996.
Find full textauthor, Quigley Tim, and Delisle R. J. author, eds. Learning Canadian criminal procedure. Toronto, Ontario: Carswell, a Division of Thomson Reuiters Canada Limited, 2013.
Find full text1943-, Stuart Don, ed. Learning Canadian criminal procedure. 2nd ed. Scarborough, Ont., Canada: Thomson Professional Pub. Canada, 1991.
Find full textDelisle, R. J. Learning Canadian criminal procedure. Toronto: Carswell, 1986.
Find full textauthor, Quigley Tim, ed. Learning Canadian criminal procedure. Toronto, Ontario: Thomson Reuters, 2016.
Find full textDelisle, R. J. Learning Canadian criminal procedure. 3rd ed. Scarborough, Ont: Carswell, 1994.
Find full textBook chapters on the topic "Procedure learning"
Goertzel, Ben, Cassio Pennachin, and Nil Geisweiller. "Integrative Procedure Learning." In Atlantis Thinking Machines, 369–89. Paris: Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-030-0_23.
Full textFalmagne, Jean-Claude, and Jean-Paul Doignon. "A Markov Chain Procedure." In Learning Spaces, 273–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-01039-2_14.
Full textGoertzel, Ben, Cassio Pennachin, and Nil Geisweiller. "Procedure Learning as Program Learning." In Atlantis Thinking Machines, 213–16. Paris: Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-030-0_12.
Full textHammer, Patrick, and Tony Lofthouse. "Goal-Directed Procedure Learning." In Artificial General Intelligence, 77–86. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97676-1_8.
Full textGoertzel, Ben, Cassio Pennachin, and Nil Geisweiller. "Probabilistic Evolutionary Procedure Learning." In Atlantis Thinking Machines, 239–71. Paris: Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-030-0_15.
Full textScheffer, Thomas, Kati Hannken-Illjes, and Alexander Kozin. "Procedural Presence: Failing and Learning." In Criminal Defence and Procedure, 117–37. London: Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230283114_5.
Full textFalmagne, Jean-Claude, and Jean-Paul Doignon. "Uncovering the Latent State: A Continuous Markov Procedure." In Learning Spaces, 241–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-01039-2_13.
Full textAmmon, Kurt. "Some experiments with a learning procedure." In Analogical and Inductive Inference, 87–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-56004-1_6.
Full textGoertzel, Ben, Cassio Pennachin, and Nil Geisweiller. "Procedure Learning via Adaptively Biased Hillclimbing." In Atlantis Thinking Machines, 227–38. Paris: Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-030-0_14.
Full textSalomon, R. "Collective Learning as an Efficient Learning and Function Optimization Procedure." In Intelligent Systems Third Golden West International Conference, 77–83. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-7108-3_10.
Full textConference papers on the topic "Procedure learning"
Chang, Chen-Huei, Chao-Chih Chang, and Shu-Yuen Hwang. "Connectionist learning procedure for edge detector." In Robotics - DL tentative, edited by David P. Casasent. SPIE, 1992. http://dx.doi.org/10.1117/12.57061.
Full textJagamogan, Reevan Seelen, Saiful Adli Ismail, Noor Hafizah Hassan, and Hafiza Abas. "Penetration Testing Procedure using Machine Learning." In 2022 4th International Conference on Smart Sensors and Application (ICSSA). IEEE, 2022. http://dx.doi.org/10.1109/icssa54161.2022.9870951.
Full textJacobs, Gilles, and Pierre Henneaux. "Unsupervised learning procedure for NILM applications." In 2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON). IEEE, 2020. http://dx.doi.org/10.1109/melecon48756.2020.9140477.
Full textLi, Lingfeng, Richard A. Paris, Conner Pinson, Yan Wang, Joseph Coco, Jamison Heard, Julie A. Adams, Daniel V. Fabbri, and Bobby Bodenheimer. "Emergency Clinical Procedure Detection With Deep Learning." In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) in conjunction with the 43rd Annual Conference of the Canadian Medical and Biological Engineering Society. IEEE, 2020. http://dx.doi.org/10.1109/embc44109.2020.9175575.
Full textShiina, Hiromitsu, Akiyoshi Takahashi, Ryunosuke Ito, and Nobuyuki Kobayashi. "Comment Generation System for Program Procedure Learning." In 2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2018. http://dx.doi.org/10.1109/iiai-aai.2018.00018.
Full textElhamifar, Ehsan, and Zwe Naing. "Unsupervised Procedure Learning via Joint Dynamic Summarization." In 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2019. http://dx.doi.org/10.1109/iccv.2019.00644.
Full textChang, Chingwei, Kwoting Fang, and Chiungyu Huang. "Dynamic Knowledge Management Procedure Using Fuzzy Clustering." In 2008 Seventh International Conference on Machine Learning and Applications. IEEE, 2008. http://dx.doi.org/10.1109/icmla.2008.99.
Full textAbas, Marcel, and Tomas Skripcak. "A modification of gradient policy in reinforcement learning procedure." In 2012 15th International Conference on Interactive Collaborative Learning (ICL). IEEE, 2012. http://dx.doi.org/10.1109/icl.2012.6402200.
Full textLei, Jun, Guohui Li, Jun Zhang, Dan Lu, and Qiang Guo. "Online structural SVM learning by dual ascending procedure." In 2014 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2014. http://dx.doi.org/10.1109/spac.2014.6982687.
Full textZhohov, Roman, Alexandros Palaios, Henrik Ryden, Reza Moosavi, and Joel Berglund. "Reducing Latency: Improving Handover Procedure Using Machine Learning." In 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring). IEEE, 2021. http://dx.doi.org/10.1109/vtc2021-spring51267.2021.9448875.
Full textReports on the topic "Procedure learning"
Goetsch, Gordon J. CONSENSUS: A Statistical Learning Procedure in a Connectionist Network. Fort Belvoir, VA: Defense Technical Information Center, December 1987. http://dx.doi.org/10.21236/ada188531.
Full textDafny, Leemore. Entry Deterrence in Hospital Procedure Markets: A Simple Model of Learning-By-Doing. Cambridge, MA: National Bureau of Economic Research, July 2003. http://dx.doi.org/10.3386/w9871.
Full textWells, Rosalie, and Joseph D. Hagman. Training Procedures for Enhancing Reserve Component Learning, Retention, and Transfer. Fort Belvoir, VA: Defense Technical Information Center, September 1989. http://dx.doi.org/10.21236/ada217450.
Full textOhlsson, Stellan. The Cognitive Function of Theoretical Knowledge in Procedural Learning. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada248075.
Full textDownard, Alicia, Stephen Semmens, and Bryant Robbins. Automated characterization of ridge-swale patterns along the Mississippi River. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40439.
Full textOhlsson, Stellan, and Ernest Reese. An Information Processing Analysis of the Function of Conceptual Understanding in the Learning of Arithmetic Procedures. Fort Belvoir, VA: Defense Technical Information Center, August 1988. http://dx.doi.org/10.21236/ada202740.
Full textPinchuk, Olga P., Oleksandra M. Sokolyuk, Oleksandr Yu Burov, and Mariya P. Shyshkina. Digital transformation of learning environment: aspect of cognitive activity of students. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3243.
Full textHefetz, Abraham, and Justin O. Schmidt. Use of Bee-Borne Attractants for Pollination of Nonrewarding Flowers: Model System of Male-Sterile Tomato Flowers. United States Department of Agriculture, October 2003. http://dx.doi.org/10.32747/2003.7586462.bard.
Full textHuang, Haohang, Erol Tutumluer, Jiayi Luo, Kelin Ding, Issam Qamhia, and John Hart. 3D Image Analysis Using Deep Learning for Size and Shape Characterization of Stockpile Riprap Aggregates—Phase 2. Illinois Center for Transportation, September 2022. http://dx.doi.org/10.36501/0197-9191/22-017.
Full textKirichek, Galina, Vladyslav Harkusha, Artur Timenko, and Nataliia Kulykovska. System for detecting network anomalies using a hybrid of an uncontrolled and controlled neural network. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3743.
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