Relevant bibliographies by topics / Classical learning

Academic literature on the topic 'Classical learning'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 January 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Classical learning.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Classical learning"

1

Khan, Tariq M., and Antonio Robles-Kelly. "Machine Learning: Quantum vs Classical." IEEE Access 8 (2020): 219275–94. http://dx.doi.org/10.1109/access.2020.3041719.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Williams, Ben A. "Rejuvenation of Classical Learning Theory." Contemporary Psychology: A Journal of Reviews 37, no. 8 (August 1992): 772–73. http://dx.doi.org/10.1037/032447.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Song Pyung-Nynul. "Application of Collaborative Learning in Teaching-Learning Classical Chinese." DONG-BANG KOREAN CHINESE LIEARATURE ll, no. 32 (June 2007): 401–23. http://dx.doi.org/10.17293/dbkcls.2007..32.401.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Wang, R., L. J. Cong, and C. Yu. "The classical TDT perceptual learning is mostly temporal learning." Journal of Vision 13, no. 5 (April 12, 2013): 9. http://dx.doi.org/10.1167/13.5.9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

CD, Diyana. "Improving Science Learning Outcomes About Material Through the Problem Based Learning Learning Model in Online Learning." Social, Humanities, and Educational Studies (SHEs): Conference Series 3, no. 4 (July 17, 2021): 429. http://dx.doi.org/10.20961/shes.v3i4.53380.

Full text
Abstract:
<em>This research was carried out with the aim of improving student learning outcomes in science subjects about material using the Problem Based Learning model for fifth grade students at SD Negeri Limbangan</em><em> 01, Losari District, Brebes Regency, for the 2019/2020 academic year with a total of 11 students.The research shows an increase in the percentage of learning outcomes, this can be seen from the KKM completeness of students from pre-cycle activities, first cycles, and second cycles. The average value of students in the initial conditions (pre-cycle) is 53.64 with classical completeness of 45%. Cycle I was 67.27 with classical completeness of 73%. Cycle II was 83.64 with 91% classical completeness. Thus, it can be concluded that the use of Problem Based Learning (PBL) in online learning can improve student learning outcomes in learning science about material</em>
APA, Harvard, Vancouver, ISO, and other styles
6

Mauliandari, Riana, Made Sumarwati, and Arif Setyo Upoyo. "Peer Learning: An Effective Teaching-Learning Method for Improving Ability in Arterial Blood Gases Interpretation." Nurse Media Journal of Nursing 10, no. 3 (December 21, 2020): 329–38. http://dx.doi.org/10.14710/nmjn.v10i3.28660.

Full text
Abstract:
Background: Competent nurses are expected to be able to interpret arterial blood gases (ABGs). The benefits of peer learning, an innovative teaching-learning method today, have long been recognized. However, to date, no studies have compared the effect of this method and the traditional classical method in interpreting ABGs. Purpose: This study aimed to compare the effect of peer learning and classical learning methods on the nurses’ ability to interpret ABGs. Method: This was a quasi-experimental research with pre and post-test design. Forty ward nurses were invited in the peer learning method group, and another 40 ward nurses were invited in the classical learning method group through a randomization process. Data were collected using a questionnaire before and after the educational intervention. The classical class was taught by an experienced trainer, while peer groups, divided into groups of 5-6, were taught by one member of each group who obtained the best pre-test score and received special training first. The analysis of data was performed by t-test.Result: The result showed that after the intervention, the mean score of interpreting ABGs in the peer learning group increased by 3.18±1.12 (p<0.001), while in the classical learning method, it only increased by 2.32±0.988 (p<0.001). Although there were significant increases in ABGs analysis’s ability in both groups, the peer teaching-learning group demonstrated a significantly greater improvement in interpreting ABGs (p<0.001).Conclusion: The peer learning method facilitates a more significant improvement in the nurses’ ability for ABGs interpretation. Peer learning is appropriate as one of the methods in clinical education for nurses.
APA, Harvard, Vancouver, ISO, and other styles
7

Ciliberto, Carlo, Mark Herbster, Alessandro Davide Ialongo, Massimiliano Pontil, Andrea Rocchetto, Simone Severini, and Leonard Wossnig. "Quantum machine learning: a classical perspective." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 474, no. 2209 (January 2018): 20170551. http://dx.doi.org/10.1098/rspa.2017.0551.

Full text
Abstract:
Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning (ML) techniques to impressive results in regression, classification, data generation and reinforcement learning tasks. Despite these successes, the proximity to the physical limits of chip fabrication alongside the increasing size of datasets is motivating a growing number of researchers to explore the possibility of harnessing the power of quantum computation to speed up classical ML algorithms. Here we review the literature in quantum ML and discuss perspectives for a mixed readership of classical ML and quantum computation experts. Particular emphasis will be placed on clarifying the limitations of quantum algorithms, how they compare with their best classical counterparts and why quantum resources are expected to provide advantages for learning problems. Learning in the presence of noise and certain computationally hard problems in ML are identified as promising directions for the field. Practical questions, such as how to upload classical data into quantum form, will also be addressed.
APA, Harvard, Vancouver, ISO, and other styles
8

Shrivastava, Prakhar, Kapil Kumar Soni, and Akhtar Rasool. "Classical Equivalent Quantum Unsupervised Learning Algorithms." Procedia Computer Science 167 (2020): 1849–60. http://dx.doi.org/10.1016/j.procs.2020.03.204.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Rihll, T. E. "Teaching and Learning in Classical Athens." Greece and Rome 50, no. 2 (October 2003): 168–90. http://dx.doi.org/10.1093/gr/50.2.168.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Schreurs, Bernard G., and Daniel L. Alkon. "Imaging learning and memory: Classical conditioning." Anatomical Record 265, no. 6 (2001): 257–73. http://dx.doi.org/10.1002/ar.10031.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Classical learning"

1

Aschieri, Federico. "Learning, realizability and games in classical arithmetic." Thesis, Queen Mary, University of London, 2011. http://qmro.qmul.ac.uk/xmlui/handle/123456789/2325.

Full text
Abstract:
Abstract. In this dissertation we provide mathematical evidence that the concept of learning can be used to give a new and intuitive computational semantics of classical proofs in various fragments of Predicative Arithmetic. First, we extend Kreisel modi ed realizability to a classical fragment of rst order Arithmetic, Heyting Arithmetic plus EM1 (Excluded middle axiom restricted to 0 1 formulas). We introduce a new realizability semantics we call \Interactive Learning-Based Realizability". Our realizers are self-correcting programs, which learn from their errors and evolve through time, thanks to their ability of perpetually questioning, testing and extending their knowledge. Remarkably, that capability is entirely due to classical principles when they are applied on top of intuitionistic logic. Secondly, we extend the class of learning based realizers to a classical version PCFClass of PCF and, then, compare the resulting notion of realizability with Coquand game semantics and prove a full soundness and completeness result. In particular, we show there is a one-to-one correspondence between realizers and recursive winning strategies in the 1-Backtracking version of Tarski games. Third, we provide a complete and fully detailed constructive analysis of learning as it arises in learning based realizability for HA+EM1, Avigad's update procedures and epsilon substitution method for Peano Arithmetic PA. We present new constructive techniques to bound the length of learning processes and we apply them to reprove - by means of our theory - the classic result of G odel that provably total functions of PA can be represented in G odel's system T. Last, we give an axiomatization of the kind of learning that is needed to computationally interpret Predicative classical second order Arithmetic. Our work is an extension of Avigad's and generalizes the concept of update procedure to the trans nite case. Trans- nite update procedures have to learn values of trans nite sequences of non computable functions in order to extract witnesses from classical proofs.
APA, Harvard, Vancouver, ISO, and other styles
2

Silkstone, Francis. "Learning Thai classical music : memorisation and improvisation." Thesis, SOAS, University of London, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388511.

Full text
Abstract:
As in other oral traditions, the core of traditional training in Thai classical music is that the student memonses music given by the teacher. Teachers offer few explanations but give musical examples that transmit each skill at the right time for the student. Training on fiddles can be understood by considering three learned elements: Basic Melody: the essential structure of each composition, encapsulated in its most tangible form as the melody played on the large gong-circle, but internalised in increasingly subtle and fluid forms as the student progresses; Realisations of each composition for fiddles, improvised by the teacher and memorised by the student during each lesson; Various techniques of improvisation (ways of realising the Basic Melody of a given composition as a new melody for fiddle). Learning how to conceptualise the Basic Melody is inseparable from gaining competence in fiddle improvisation. Teachers' explanations concerning melodies they teach suggest transmission of a highly flexible conceptualisation of Basic Melody and a complex technique of improvisation. Three etic explanations of the latter are: 'Filling-in': the player inserts notes between the notes of the less dense Basic Melody so that the fiddle melody conforms to each pitch of the Basic Melody. 'Idiomatic elaboration': a fiddle melody is derived from the Basic Melody according to a musical 'grammar' in which every pitch need not conform to the v Basic Melody, though many pitches are likely to do so. Formulaic manipulation: for each Basic Melody formula, the fiddle player chooses one of several eligible fiddle-formulas, then spontaneously adjusts it in a manner appropriate to that context and moment. These three are sometimes alternative explanations of the same process, sometimes distinct processes. In each rendition, a teacher moves between the three processes. All three are necessary to the complexities and beautiful ambiguities of musical thought.
APA, Harvard, Vancouver, ISO, and other styles
3

Jovanovic, Filip, and Paul Singh. "Modelling default probabilities: The classical vs. machine learning approach." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273570.

Full text
Abstract:
Fintech companies that offer Buy Now, Pay Later products are heavily dependent on accurate default probability models. This is since the fintech companies bear the risk of customers not fulfilling their obligations. In order to minimize the losses incurred to customers defaulting several machine learning algorithms can be applied but in an era in which machine learning is gaining popularity, there is a vast amount of algorithms to select from. This thesis aims to address this issue by applying three fundamentally different machine learning algorithms in order to find the best algorithm according to a selection of chosen metrics such as ROCAUC and precision-recall AUC. The algorithms that were compared are Logistic Regression, Random Forest and CatBoost. All these algorithms were benchmarked against Klarna's current XGBoost model. The results indicated that the CatBoost model is the optimal one according to the main metric of comparison, the ROCAUC-score. The CatBoost model outperformed the Logistic Regression model by seven percentage points, the Random Forest model by three percentage points and the XGBoost model by one percentage point.
Fintechbolag som erbjuder Köp Nu, Betala Senare-tjänster är starkt beroende av välfungerande fallissemangmodeller. Detta då dessa fintechbolag bär risken av att kunder inte betalar tillbaka sina krediter. För att minimera förlusterna som uppkommer när en kund inte betalar tillbaka finns flera olika maskininlärningsalgoritmer att applicera, men i dagens explosiva utveckling på maskininlärningsfronten finns det ett stort antal algoritmer att välja mellan. Denna avhandling ämnar att testa tre olika maskininlärningsalgoritmer för att fastställa vilken av dessa som presterar bäst sett till olika prestationsmått så som ROCAUC och precision-recall AUC. Algoritmerna som jämförs är Logistisk Regression, Random Forest och CatBoost. Samtliga algoritmers prestanda jämförs även med Klarnas nuvarande XGBoost-modell. Resultaten visar på att CatBoost-modellen är den mest optimala sett till det primära prestationsmåttet ROCAUC. CatBoost-modellen var överlägset bättre med sju procentenheter högre ROCAUC än Logistisk Regression, tre procentenheter högre ROCAUC än Random Forest och en procentenhet högre ROCAUC än Klarnas nuvarande XGBoost-modell
APA, Harvard, Vancouver, ISO, and other styles
4

Dukes, Kais. "Statistical parsing by machine learning from a Classical Arabic treebank." Thesis, University of Leeds, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.658551.

Full text
Abstract:
Research into statistical parsing for English has enjoyed over a decade of successful results. However, adapting these models to other languages has met with difficulties. Previous comparative work has shown that Modern Arabic is one of the most difficult languages to parse due to rich morphology and free word order. Classical Arabic is the ancient form of Arabic, and is understudied in computational linguistics, relative to its worldwide reach as the language of the Quran. The thesis is based on seven publications that make significant contributions to knowledge relating to annotating and parsing Classical Arabic. Classical Arabic has been studied in depth by grammarians for over a thousand years using a traditional grammar known as i'rab. Using this grammar to develop a representation for parsing is challenging, as it describes syntax using a hybrid of phrase-structure and dependency relations. This work aims to advance the state-of-the-art for hybrid parsing by introducing a formal representation for annotation and a resource for machine learning. The main contributions are the first treebank for Classical Arabic and the first statistical dependency-based parser in any language for ellipsis, dropped pronouns and hybrid representations. A central argument of this thesis is that using a hybrid representation closely aligned to traditional grammar leads to improved parsing for Arabic. To test this hypothesis, two approaches are compared. As a reference, a pure dependency parser is adapted using graph transformations, resulting in an 87.47% F I-score. This is compared to an integrated parsing model with an F I-score of 89.03%, demonstrating that joint dependency-constituency parsing is better suited to Classical Arabic. The Quran was chosen for annotation as a large body of work exists providing detailed syntactic analysis. Volunteer crowdsourcing is used for annotation in combination with expert supervision. A practical result of the annotation effort is the corpus website: http://corpus.quran.com, an educational resource with over two million users per year.
APA, Harvard, Vancouver, ISO, and other styles
5

Pesah, Arthur. "Learning quantum state properties with quantum and classical neural networks." Thesis, KTH, Tillämpad fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252693.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Soanes, Grant Paul. "Visual and chemical learning in the pond snail, Lymnaea stagnalis." Thesis, University of Sussex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285369.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Bertolucci, Franco. "Operant and classical learning in Drosophila melanogaster: the ignorant gene (ign)." kostenfrei, 2008. http://www.opus-bayern.de/uni-wuerzburg/volltexte/2009/3398/.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Murphy, Robin A. J. "Relative contingency learning in Pavlovian conditioning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0026/NQ50226.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Bodén, Johan. "A Comparative Study of Reinforcement-­based and Semi­-classical Learning in Sensor Fusion." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-84784.

Full text
Abstract:
Reinforcement learning has proven itself very useful in certain areas, such as games. However, the approach has been seen as quite limited. Reinforcement-based learning has for instance not been commonly used for classification tasks as it is receiving feedback on how well it did for an action performed on a specific input. This slows the performance convergence rate as compared to other classification approaches which has the input and the corresponding output to train on. Nevertheless, this thesis aims to investigate whether reinforcement-based learning could successfully be employed on a classification task. Moreover, as sensor fusion is an expanding field which can for instance assist autonomous vehicles in understanding its surroundings, it is also interesting to see how sensor fusion, i.e., fusion between lidar and RGB images, could increase the performance in a classification task. In this thesis, a reinforcement-based learning approach is compared to a semi-classical approach. As an example of a reinforcement learning model, a deep Q-learning network was chosen, and a support vector machine classifier built on top of a deep neural network, was chosen as an example of a semi-classical model. In this work, these frameworks are compared with and without sensor fusion to see whether fusion improves their performance. Experiments show that the evaluated reinforcement-based learning approach underperforms in terms of metrics but mainly due to its slow learning process, in comparison to the semi-classical approach. However, on the other hand using reinforcement-based learning to carry out a classification task could still in some cases be advantageous, as it still performs fairly well in terms of the metrics presented in this work, e.g. F1-score, or for instance imbalanced datasets. As for the impact of sensor fusion, a notable improvement can be seen, e.g. when training the deep Q-learning model for 50 episodes, the F1-score increased with 0.1329; especially, when taking into account that the most of the lidar data used in the fusion is lost since this work projects the 3D lidar data onto the same 2D plane as the RGB images.
APA, Harvard, Vancouver, ISO, and other styles
10

Prato, D. E. "Developing unification in the teaching and learning of jazz and classical guitar." Thesis, University of Salford, 2017. http://usir.salford.ac.uk/43486/.

Full text
Abstract:
I am a guitarist who dedicates to the styles of jazz and classical music. After starting out by playing folk and rock styles during my childhood, I later gravitated towards blues and funk and eventually jazz in my late teens, when I decided to become a full time musician. Later, in my mid twenties, I developed a passion for the classical guitar and eventually made the decision to dedicate 50% of my practice time to this style and 50% to jazz. Inevitably, as a result of a serious commitment to both styles, I have had a personal experience of what their study involves, how their value systems work and what aspects of music and guitar performance they each prioritize. I have found this experience deeply interesting because they both have developed a very advanced understanding of the instrument, but in very different areas. The first intention of this thesis is to identify what the differences are in the ideologies, teaching and learning of the guitar between the jazz and the classical genres. I then will contemplate whether a potential for an enhanced understanding of the instrument as a whole can be achieved in the future through the process of these styles each absorbing knowledge developed by the other. The research has been undertaken in the area of literature and instructional material for the instrument, as well as through interviews with guitarists in both fields. Additionally, I have included a chapter based on a reflective analysis of my own experience as a student of both genres. In order to facilitate the understanding of why these styles have developed in the way that they have, there is also a chapter dedicated to the historical context of the genres. Based on my findings, I have included a conclusion in the form of lessons aimed at guitarists in each style, presenting to them ways in which they can advance their understanding of the instrument based on knowledge developed within each other’s schools and ideologies. Finally, I have also created a DVD to support this proposal, with relevant demonstrations and performances on the instrument. These doctoral studies have conformed one of the most significant learning periods in my life as a musician and guitarist. I am fascinated by this subject and will continue to work on it through my ongoing research, playing and teaching. I hope that this work will help to generate more interest and research in this area of guitar playing.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Classical learning"

1

Donaldson, John William. Classical scholarship and classical learning: Considered with especial reference to ... [S.l.]: Cambridge University Pres, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Lee, Too Yun, and Livingstone Niall, eds. Pedagogy and power: Rhetorics of classical learning. Cambridge: Cambridge University Press, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Religion, law, and learning in classical Islam. Hampshire, Great Britain: Variorum, 1991.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Plotkin, Fred. Classical music unbuttoned: A complete guide to learning and loving classical music. London: Aurum, 2003.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

History of classical scholarship from 1300 to 1850. Oxford: Clarendon Press, 1999.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Goddard, Murray. Animal learning: Greatest hits. Dubuque, Iowa: W.C. Brown, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Democracy and knowledge: Innovation and learning in classical Athens. Princeton: Princeton University Press, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

The classical heritage in Islam. London: Routledge, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

1955-, Steinmetz Joseph E., ed. Handbook of classical conditioning. Boston: Kluwer Academic Publishers, 2003.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Edwin, Sandys John. A history of classical scholarship. Mansfield Center, CT: Martino Pub., 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Classical learning"

1

Kohonen, Teuvo. "Classical Learning Systems." In Self-Organization and Associative Memory, 68–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-88163-3_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Kohonen, Teuvo. "Classical Learning Systems." In Self-Organization and Associative Memory, 68–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-662-00784-6_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Shavlik, Jude W. "Learning Classical Physics." In The Kluwer International Series in Engineering and Computer Science, 307–10. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4613-2279-5_62.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Guzdial, Matthew, Sam Snodgrass, and Adam J. Summerville. "Classical PCG." In Procedural Content Generation via Machine Learning, 7–22. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16719-5_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Xu, Long, Yihua Yan, and Xin Huang. "Classical Deep Learning Models." In Deep Learning in Solar Astronomy, 7–17. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2746-1_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Krahenbuhl, Kevin S. "The Trivium: A Classical Method." In Building Effective Learning Environments, 51–64. New York, NY: Routledge, 2021.: Routledge, 2021. http://dx.doi.org/10.4324/9781003157441-6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Reimers, Mark. "Classical Statistical Learning in Bioinformatics." In Knowledge-Based Bioinformatics, 107–23. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470669716.ch5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Servedio, Rocco A. "Separating Quantum and Classical Learning." In Automata, Languages and Programming, 1065–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-48224-5_86.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Fernández, Alberto, Salvador García, Mikel Galar, Ronaldo C. Prati, Bartosz Krawczyk, and Francisco Herrera. "Non-classical Imbalanced Classification Problems." In Learning from Imbalanced Data Sets, 305–25. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98074-4_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Schmajuk, Nestor A. "Computational Models of Classical Conditioning." In Encyclopedia of the Sciences of Learning, 700–707. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-1428-6_528.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Classical learning"

1

Ertugrul, Omer Faruk, and Mehmet Emin Tagluk. "Learning with classical conditioning." In 2014 22nd Signal Processing and Communications Applications Conference (SIU). IEEE, 2014. http://dx.doi.org/10.1109/siu.2014.6830382.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Kusnadi and Supriyadi Hasta Nugraha. "Classical Javanese Dance Learning with Blended Learning." In 2nd International Conference on Technology and Educational Science (ICTES 2020). Paris, France: Atlantis Press, 2021. http://dx.doi.org/10.2991/assehr.k.210407.223.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Brakerski, Zvika, Adeline Langlois, Chris Peikert, Oded Regev, and Damien Stehlé. "Classical hardness of learning with errors." In the 45th annual ACM symposium. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2488608.2488680.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Nieto-Chaupis, Huber. "Testing Machine Learning at Classical Electrodynamics." In 2021 6th International Conference on Smart and Sustainable Technologies (SpliTech). IEEE, 2021. http://dx.doi.org/10.23919/splitech52315.2021.9566432.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Rybina, Iryna, and Gulmyra Myrzaeva. "LEARNING ENGLISH THROUGH MOVIES AND TV SHOWS." In SCIENTIFIC PRACTICE: MODERN AND CLASSICAL RESEARCH METHODS. European Scientific Platform, 2021. http://dx.doi.org/10.36074/logos-26.02.2021.v2.27.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Vysochina, Irina. "ANALYSIS OF THE RESULTS OF DISTANCE LEARNING OF MEDICAL STUDENTS." In SCIENTIFIC PRACTICE: MODERN AND CLASSICAL RESEARCH METHODS, Chair Irina Avramenko, Nataliіa Bashkirova, and Volodymyr Kramarchuk. European Scientific Platform, 2021. http://dx.doi.org/10.36074/logos-26.02.2021.v2.24.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Sridharan, Anusha, Melody Moh, and Teng-Sheng Moh. "Similarity Estimation for Classical Indian Music." In 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2018. http://dx.doi.org/10.1109/icmla.2018.00130.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Ståhlberg, Simon, Guillem Francès, and Jendrik Seipp. "Learning Generalized Unsolvability Heuristics for Classical Planning." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/574.

Full text
Abstract:
Recent work in classical planning has introduced dedicated techniques for detecting unsolvable states, i.e., states from which no goal state can be reached. We approach the problem from a generalized planning perspective and learn first-order-like formulas that characterize unsolvability for entire planning domains. We show how to cast the problem as a self-supervised classification task. Our training data is automatically generated and labeled by exhaustive exploration of small instances of each domain, and candidate features are automatically computed from the predicates used to define the domain. We investigate three learning algorithms with different properties and compare them to heuristics from the literature. Our empirical results show that our approach often captures important classes of unsolvable states with high classification accuracy. Additionally, the logical form of our heuristics makes them easy to interpret and reason about, and can be used to show that the characterizations learned in some domains capture exactly all unsolvable states of the domain.
APA, Harvard, Vancouver, ISO, and other styles
9

Yulianti, Lenny Putri, Judhi Santoso, Agung Trisetyarso, and Kridanto Surendro. "Hybrid Classical-Quantum Optimization for Ensemble Learning." In 2022 9th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA). IEEE, 2022. http://dx.doi.org/10.1109/icaicta56449.2022.9932950.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Martinez-Martin, Ester, and Angelo Costa. "MATHS FOR ENGINEERING: PARTING FROM CLASSICAL METHODS." In 14th International Conference on Education and New Learning Technologies. IATED, 2022. http://dx.doi.org/10.21125/edulearn.2022.0245.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Classical learning"

1

Lin, Yen Ting, and Marian Anghel. Solving classical inference problems on modern machine-learning platforms. Office of Scientific and Technical Information (OSTI), February 2020. http://dx.doi.org/10.2172/1597325.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Murphy, Sean, Mohini Bariya, Debbie Chang, Jeff Lin, Chris Ryan, and Ramiro Mata. Combinatorial Evaluation of Physical Feature Engineering, Classical Machine Learning, and Deep Learning Models for Synchrophasor Data at Scale. Office of Scientific and Technical Information (OSTI), April 2022. http://dx.doi.org/10.2172/1864556.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Spataru, Dan, Matthew Witman, and Reese Jones. Tuning the critical Li intercalation concentrations for MoX2 bilayer phase transitions using classical and machine learning approaches. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1673449.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Farhi, Edward, and Hartmut Neven. Classification with Quantum Neural Networks on Near Term Processors. Web of Open Science, December 2020. http://dx.doi.org/10.37686/qrl.v1i2.80.

Full text
Abstract:
We introduce a quantum neural network, QNN, that can represent labeled data, classical or quantum, and be trained by supervised learning. The quantum circuit consists of a sequence of parameter dependent unitary transformations which acts on an input quantum state. For binary classification a single Pauli operator is measured on a designated readout qubit. The measured output is the quantum neural network’s predictor of the binary label of the input state. We show through classical simulation that parameters can be found that allow the QNN to learn to correctly distinguish the two data sets. We then discuss presenting the data as quantum superpositions of computational basis states corresponding to different label values. Here we show through simulation that learning is possible. We consider using our QNN to learn the label of a general quantum state. By example we show that this can be done. Our work is exploratory and relies on the classical simulation of small quantum systems. The QNN proposed here was designed with near-term quantum processors in mind. Therefore it will be possible to run this QNN on a near term gate model quantum computer where its power can be explored beyond what can be explored with simulation.
APA, Harvard, Vancouver, ISO, and other styles
5

Falfushynska, Halina I., Bogdan B. Buyak, Hryhorii V. Tereshchuk, Grygoriy M. Torbin, and Mykhailo M. Kasianchuk. Strengthening of e-learning at the leading Ukrainian pedagogical universities in the time of COVID-19 pandemic. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4442.

Full text
Abstract:
Distance education has become the mandatory component of higher education establishments all over the world including Ukraine regarding COVID-19 lockdown and intentions of Universities to render valuable knowledge and provide safe educational experience for students. The present study aimed to explore the student’s and academic staff’s attitude towards e-learning and the most complicated challenges regarding online learning and distance education. Our findings disclosed that the online learning using Zoom, Moodle, Google Meet, BigBlueButton and Cisco has become quite popular among the students and academic staff in Ukraine in time of the lockdown period and beyond. Based on the Principal Component Analysis data processing we can conclude that students’ satisfaction and positive e-learning perception are in a good correlation with quality of e-learning resources and set of apps which are used while e-learning and distance education. Also, education style, methods, and manner predict willingness of students to self-study. The self-motivation, time-management, lack of practice, digital alienation, positive attitude towards ICT, and instruction strategy belong to the most important challenges of COVID-19 lockdown based on the students and academic staff interviews. Online learning on daily purpose should be used in the favor of strengthening of classical higher education rather than replacing the former. Blended education is the best alternative to face-to-face education, because the communication with mentor in a live environmental even virtual should have ushered the learners to complete online learning and improve its results.
APA, Harvard, Vancouver, ISO, and other styles
6

Valencia, Oscar, Juan José Díaz, and Diego A. Parra. Assessing Macro-Fiscal Risk for Latin American and Caribbean Countries. Inter-American Development Bank, November 2022. http://dx.doi.org/10.18235/0004530.

Full text
Abstract:
This paper provides a comprehensive early warning system (EWS) that balances the classical signaling approach with the best-realized machine learning (ML) model for predicting fiscal stress episodes. Using accumulated local effects (ALE), we compute a set of thresholds for the most informative variables that drive the correlation between predictors. In addition, to evaluate the main country risks, we propose a leading fiscal risk indicator, highlighting macro, fiscal and institutional attributes. Estimates from different models suggest significant heterogeneity among the most critical variables in determining fiscal risk across countries. While macro variables have higher relevance for advanced countries, fiscal variables were more significant for Latin American and Caribbean (LAC) and emerging economies. These results are consistent under different liquidity-solvency metrics and have deepened since the global financial crisis.
APA, Harvard, Vancouver, ISO, and other styles
7

Shalatska, Hanna M., Olena Yu Zotova-Sadylo, and Ivan O. Muzyka. Moodle course in teaching English language for specific purposes for masters in mechanical engineering. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3881.

Full text
Abstract:
The central thesis of this paper is that e-learning courses can have a significant impact on English language for specific purposes (ESP) proficiency of mining mechanical engineering students. The purpose of this study is to assess the effectiveness of ESP Moodle-based course “English for Mining Mechanical Engineers” and to reveal the results of its experimental approbation. In order to identify the lectures’ and learners’ needs we have applied the survey research. The survey confirmed the greatest demand for Moodle courses that include all the elements of a coherent training manual to provide self-development of engineering students. The interview results contributed to design of author’s ESP course syllabus. The importance and originality of this study are that to approbate the course materials’ effectiveness two approaches have been adopted simultaneously. The first is blended learning method based on e-learning platform applied in the experimental group and the second one is classic in-class instructor-led studying used in a control group. Students’ progress in ESP proficiency has been assessed using the cross assessment method. The experiment has validated the initial hypothesis that the special online courses focused on honing foreign language skills and integrated in the domain of specific professional knowledge have a beneficial effect on students’ communicative competencies in general. There were identified the advantages of self-tuition based on Moodle platform. The Moodle course lets the teachers save considerable in-class time to focus more on communicative assignments. The findings of this study have a number of practical implications in ESP online courses development.
APA, Harvard, Vancouver, ISO, and other styles
8

Küsters, Ralf, and Ralf Molitor. Computing Least Common Subsumers in ALEN. Aachen University of Technology, 2000. http://dx.doi.org/10.25368/2022.110.

Full text
Abstract:
Computing the least common subsumer (lcs) in description logics is an inference task first introduced for sublanguages of CLASSIC. Roughly speaking, the lcs of a set of concept descriptions is the most specific concept description that subsumes all of the input descriptions. As such, the lcs allows to extract the commonalities from given concept descriptions, a task essential for several applications like, e.g., inductive learning, information retrieval, or the bottom-up construction of KR-knowledge bases. Previous work on the lcs has concentrated on description logics that either allow for number restrictions or for existential restrictions. Many applications, however, require to combine these constructors. In this work, we present an lcs algorithm for the description logic ALEN, which allows for both constructors (as well as concept conjunction, primitive negation, and value restrictions). The proof of correctness of our lcs algorithm is based on an appropriate structural characterization of subsumption in ALEN also introduced in this paper.
APA, Harvard, Vancouver, ISO, and other styles
9

Küsters, Ralf, and Ralf Molitor. Computing Least Common Subsumers in ALEN. Aachen University of Technology, 2000. http://dx.doi.org/10.25368/2022.110.

Full text
Abstract:
Computing the least common subsumer (lcs) in description logics is an inference task first introduced for sublanguages of CLASSIC. Roughly speaking, the lcs of a set of concept descriptions is the most specific concept description that subsumes all of the input descriptions. As such, the lcs allows to extract the commonalities from given concept descriptions, a task essential for several applications like, e.g., inductive learning, information retrieval, or the bottom-up construction of KR-knowledge bases. Previous work on the lcs has concentrated on description logics that either allow for number restrictions or for existential restrictions. Many applications, however, require to combine these constructors. In this work, we present an lcs algorithm for the description logic ALEN, which allows for both constructors (as well as concept conjunction, primitive negation, and value restrictions). The proof of correctness of our lcs algorithm is based on an appropriate structural characterization of subsumption in ALEN also introduced in this paper.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Classical learning' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography