The Linear Session Abstract Machine

Συγγραφείς: Caires, Luís, Toninho, Bernardo

Πηγή: ACM Transactions on Programming Languages and Systems. 48(3):1-66

Διαθεσιμότητα: http://dl.acm.org/doi/10.1145/3819583

Visualizing Semantic Methods: A Web-Based Educational Tool for Imperative Languages

Συγγραφείς: Tsimbolynets, Vitalii, Perhac, Jan, Novotny, Samuel

Πηγή: 2025 International Conference on Emerging eLearning Technologies and Applications (ICETA) Emerging eLearning Technologies and Applications (ICETA), 2025 International Conference on. :807-813 Nov, 2025

Relation: 2025 International Conference on Emerging eLearning Technologies and Applications (ICETA)

On Recursion in Graded Modal Type Theory

Συγγραφείς: Eriksson, Oskar, 1997, Author, Abel, Andreas Martin, 1974, Author, Danielsson, Nils Anders, 1979, Author

Συνεισφορές: Eriksson, Oskar, 1997, Author, Abel, Andreas Martin, 1974, Author, Danielsson, Nils Anders, 1979, Author

Πηγή: Proceedings of the ACM on Programming Languages. 10(ICFP)

Θεματικοί όροι: Computer Sciences, Datavetenskap (datalogi), abstract machine, dependent types, formalization, graded modal type theory, linearity, quantitative type theory

Σύνδεσμος πρόσβασης: https://gup.ub.gu.se/publication/366536

Hygienic Macros via Staged Environment Machines (Position Paper)

Συγγραφείς: Murase, Yuito

Πηγή: Proceedings of the 26th ACM SIGPLAN International Workshop on Scheme and Functional Programming. :42-47

Διαθεσιμότητα: http://dl.acm.org/doi/10.1145/3759537.3762695

Plinth: A Plugin-Powered Language Built on Haskell (Experience Report)

Συγγραφείς: Liu, Ziyang, MacKenzie, Kenneth, Kireev, Roman, Peyton Jones, Michael, Wadler, Philip, Chakravarty, Manuel

Πηγή: Proceedings of the 18th ACM SIGPLAN International Haskell Symposium. :30-37

Διαθεσιμότητα: http://dl.acm.org/doi/10.1145/3759164.3759347

Closure Conversion, Flat Environments, and the Complexity of Abstract Machines

Συγγραφείς: Accattoli, Beniamino, Belo Lourenço, Cláudio, R. Ghica, Dan, Guerrieri, Giulio, Sacerdoti Coen, Claudio

Πηγή: Proceedings of the 27th International Symposium on Principles and Practice of Declarative Programming. :1-15

Διαθεσιμότητα: http://dl.acm.org/doi/10.1145/3756907.3756922

Design of an Automatic Washing Machine Control System using Deterministic Finite Automata

Συγγραφείς: Madhuja, C, Bhanot, Shreya, M, Srinidhi, Radha, D.

Πηγή: 2024 5th IEEE Global Conference for Advancement in Technology (GCAT) Advancement in Technology (GCAT), 2024 5th IEEE Global Conference for. :1-5 Oct, 2024

Relation: 2024 5th IEEE Global Conference for Advancement in Technology (GCAT)

The Relational Machine Calculus

Συγγραφείς: Barrett, Chris, Castle, Daniel, Heijltjes, Willem

Πηγή: Proceedings of the 39th Annual ACM/IEEE Symposium on Logic in Computer Science. :1-15

Διαθεσιμότητα: http://dl.acm.org/doi/10.1145/3661814.3662091

From Complementary to Zipper Semantics

Συγγραφείς: Lenglet, Sergueï^Aff9, Noûs, Camille^Aff10, Schmitt, Alan^Aff11

Συνεισφορές: Goos, Gerhard, Founding Editor^Aff1, Hartmanis, Juris, Founding Editor^Aff2, Bertino, Elisa, Editorial Board Member^Aff3, Gao, Wen, Editorial Board Member^Aff4, Steffen, Bernhard, Editorial Board Member^Aff5, Yung, Moti, Editorial Board Member^Aff6, Mezzina, Claudio Antares, editor^Aff7, Schmitt, Alan, editor^Aff8

Πηγή: Components Operationally: Reversibility and System Engineering : Essays Dedicated to Jean-Bernard Stefani on the Occasion of His 65th Birthday. 16065:89-102

The Sparse Abstract Machine

Συγγραφείς: Hsu, Olivia, Strange, Maxwell, Sharma, Ritvik, Won, Jaeyeon, Olukotun, Kunle, Emer, Joel S., Horowitz, Mark A., Kjølstad, Fredrik

Πηγή: Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3. :710-726

Διαθεσιμότητα: http://dl.acm.org/doi/10.1145/3582016.3582051

Software tool for supporting the experiential teaching of selected methods of formal semantics

Συγγραφείς: Kravcova, Jana, Steingartner, William, Buckova, Hana

Πηγή: 2021 19th International Conference on Emerging eLearning Technologies and Applications (ICETA) Emerging eLearning Technologies and Applications (ICETA), 2021 19th International Conference on. :197-203 Nov, 2021

Relation: 2021 19th International Conference on Emerging eLearning Technologies and Applications (ICETA)

Compiler Module of Abstract Machine Code for Formal Semantics Course

Συγγραφείς: Steingartner, William

Πηγή: 2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Applied Machine Intelligence and Informatics (SAMI), 2021 IEEE 19th World Symposium on. :000193-000200 Jan, 2021

Relation: 2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)

Measuring the Quality of B Abstract Machines with ISO/IEC 25010

Συγγραφείς: Cai, Cheng-Hao, Sun, Jing, Dobbie, Gillian

Πηγή: 2020 International Symposium on Theoretical Aspects of Software Engineering (TASE) TASE Theoretical Aspects of Software Engineering (TASE),2020 International Symposium on. :169-176 Dec, 2020

Relation: 2020 International Symposium on Theoretical Aspects of Software Engineering (TASE)

ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing

Συγγραφείς: Tan, C., Xie, C., Geng, T., Marquez, A., Tumeo, A., Barker, K., Li, A.

Πηγή: IEEE Transactions on Parallel and Distributed Systems IEEE Trans. Parallel Distrib. Syst. Parallel and Distributed Systems, IEEE Transactions on. 32(12):2880-2892 Dec, 2021

AMPPERE : A Universal Abstract Machine for Privacy-Preserving Entity Resolution Evaluation

Συγγραφείς: Yao, Yixiang, Ghai, Tanmay, Ravi, Srivatsan, Szekely, Pedro

Πηγή: Proceedings of the 30th ACM International Conference on Information & Knowledge Management. :2394-2403

Διαθεσιμότητα: http://dl.acm.org/doi/10.1145/3459637.3482318

Vers la complétude interactive: exigences pour une machine abstraite orientée interaction : Toward Interactive Completeness: Requirements for an Interactive Abstract Machine

Συγγραφείς: Martin, Alice, Magnaudet, Mathieu, Conversy, Stephane

Πηγή: Adjunct Proceedings of the 32nd Conference on l'Interaction Homme-Machine. :1-6

Διαθεσιμότητα: http://dl.acm.org/doi/10.1145/3451148.3458644

A predictive analysis for detecting deadlock in MPI programs

Συγγραφείς: Huang, Yu, Ogles, Benjamin, Mercer, Eric

Πηγή: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering. :18-28

Διαθεσιμότητα: http://dl.acm.org/doi/10.1145/3324884.3416588

Zilch: A Framework for Deploying Transparent Zero-Knowledge Proofs

Συγγραφείς: Mouris, D., Tsoutsos, N.G.

Πηγή: IEEE Transactions on Information Forensics and Security IEEE Trans.Inform.Forensic Secur. Information Forensics and Security, IEEE Transactions on. 16:3269-3284 2021

B-Repair: Repairing B-Models Using Machine Learning

Συγγραφείς: Cai, Cheng-Hao, Sun, Jing, Dobbie, Gillian

Πηγή: 2018 23rd International Conference on Engineering of Complex Computer Systems (ICECCS) ICECCS Engineering of Complex Computer Systems (ICECCS), 2018 23rd International Conference on. :31-40 Dec, 2018

Relation: 2018 23rd International Conference on Engineering of Complex Computer Systems (ICECCS)

THEORETICAL ASPECTS OF MACHINE LEARNING IN STATISTICAL DATA PROCESSING

Συγγραφείς: M.Mukhitdinova

Θεματικοί όροι: Abstract: Machine learning (ML) has emerged as a powerful tool in the field of statistical data processing, enabling the analysis and extraction of insights from complex datasets. This theoretical study explores the fundamental concepts of machine learning in the context of statistical data processing, highlighting its application in various domains such as data mining, predictive analytics, and pattern recognition. Key principles of ML, including supervised and unsupervised learning, model selection, overfitting, and validation techniques, are discussed in relation to statistical methods. The integration of machine learning algorithms with statistical models provides a robust framework for analyzing large-scale data, enhancing predictive accuracy and decision-making processes. Furthermore, the paper examines challenges associated with the implementation of ML in statistical data processing, such as data quality, computational complexity, and interpretability of results. Theoretical advancements in ML, such as deep learning and ensemble methods, are also reviewed for their impact on improving statistical models. The study concludes by emphasizing the growing importance of machine learning in modern statistical analysis and its potential to revolutionize data-driven decision-making. Keywords: machine learning, statistical learning, supervised learning, unsupervised learning, reinforcement learning, risk minimization, regularization, optimization, probabilistic models, deep learning