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Relevant bibliographies by topics / Batches of task graphs

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Academic literature on the topic 'Batches of task graphs'

Author: Grafiati

Published: 25 May 2024

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Journal articles on the topic "Batches of task graphs"

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DIAKITÉ, SÉKOU, LORIS MARCHAL, JEAN-MARC NICOD, and LAURENT PHILIPPE. "PRACTICAL STEADY-STATE SCHEDULING FOR TREE-SHAPED TASK GRAPHS." Parallel Processing Letters 21, no. 04 (2011): 397–412. http://dx.doi.org/10.1142/s0129626411000291.

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In this paper, we focus on the problem of scheduling a collection of similar task graphs on a heterogeneous platform, when the task graph is an intree. We rely on steady-state scheduling techniques, and aim at optimizing the throughput of the system. Contrarily to previous studies, we concentrate on practical aspects of steady-state scheduling, when dealing with a collection (or batch) of limited size. We focus here on two optimizations. The first one consists in reducing the processing time of each task graph, thus making steady-state scheduling applicable to smaller batches. The second one c

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Wang, Xun, Chaogang Zhang, Ying Zhang, et al. "IMGG: Integrating Multiple Single-Cell Datasets through Connected Graphs and Generative Adversarial Networks." International Journal of Molecular Sciences 23, no. 4 (2022): 2082. http://dx.doi.org/10.3390/ijms23042082.

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There is a strong need to eliminate batch-specific differences when integrating single-cell RNA-sequencing (scRNA-seq) datasets generated under different experimental conditions for downstream task analysis. Existing batch correction methods usually transform different batches of cells into one preselected “anchor” batch or a low-dimensional embedding space, and cannot take full advantage of useful information from multiple sources. We present a novel framework, called IMGG, i.e., integrating multiple single-cell datasets through connected graphs and generative adversarial networks (GAN) to el

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Wang, Yue, Ruiqi Xu, Xun Jian, Alexander Zhou, and Lei Chen. "Towards distributed bitruss decomposition on bipartite graphs." Proceedings of the VLDB Endowment 15, no. 9 (2022): 1889–901. http://dx.doi.org/10.14778/3538598.3538610.

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Mining cohesive subgraphs on bipartite graphs is an important task. The k -bitruss is one of many popular cohesive subgraph models, which is the maximal subgraph where each edge is contained in at least k butterflies. The bitruss decomposition problem is to find all k -bitrusses for k ≥ 0. Dealing with large graphs is often beyond the capability of a single machine due to its limited memory and computational power, leading to a need for efficiently processing large graphs in a distributed environment. However, all current solutions are for a single machine and a centralized environment, where

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Jia, Haozhang. "Graph sampling based deep metric learning for cross-view geo-localization." Journal of Physics: Conference Series 2711, no. 1 (2024): 012004. http://dx.doi.org/10.1088/1742-6596/2711/1/012004.

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Abstract Cross-view geo-localization has emerged as a novel computer vision task that has garnered increasing attention. This is primarily attributed to its practical significance in the domains of drone navigation and drone-view localization. Moreover, the work is particularly demanding due to its inherent requirement for cross-domain matching. There are generally two ways to train a neural network to match similar satellite and drone-view images: presentation learning with classifiers and identity loss, and metric learning with pairwise matching within mini-batches. The first takes extra com

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Angriman, Eugenio, Michał Boroń, and Henning Meyerhenke. "A Batch-dynamic Suitor Algorithm for Approximating Maximum Weighted Matching." ACM Journal of Experimental Algorithmics 27 (December 31, 2022): 1–41. http://dx.doi.org/10.1145/3529228.

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Matching is a popular combinatorial optimization problem with numerous applications in both commercial and scientific fields. Computing optimal matchings w.r.t. cardinality or weight can be done in polynomial time; still, this task can become infeasible for very large networks. Thus, several approximation algorithms that trade solution quality for a faster running time have been proposed. For networks that change over time, fully dynamic algorithms that efficiently maintain an approximation of the optimal matching after a graph update have been introduced as well. However, no semi- or fully dy

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Zhang, Xin, Yanyan Shen, Yingxia Shao, and Lei Chen. "DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU." Proceedings of the ACM on Management of Data 1, no. 2 (2023): 1–24. http://dx.doi.org/10.1145/3589311.

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Recently Graph Neural Networks (GNNs) have achieved great success in many applications. The mini-batch training has become the de-facto way to train GNNs on giant graphs. However, the mini-batch generation task is extremely expensive which slows down the whole training process. Researchers have proposed several solutions to accelerate the mini-batch generation, however, they (1) fail to exploit the locality of the adjacency matrix, (2) cannot fully utilize the GPU memory, and (3) suffer from the poor adaptability to diverse workloads. In this work, we propose DUCATI, aDual-Cache system to over

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Vo, Tham, and Phuc Do. "GOW-Stream: A novel approach of graph-of-words based mixture model for semantic-enhanced text stream clustering." Intelligent Data Analysis 25, no. 5 (2021): 1211–31. http://dx.doi.org/10.3233/ida-205443.

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Recently, rapid growth of social networks and online news resources from Internet have made text stream clustering become an insufficient application in multiple domains (e.g.: text retrieval diversification, social event detection, text summarization, etc.) Different from traditional static text clustering approach, text stream clustering task has specific key challenges related to the rapid change of topics/clusters and high-velocity of coming streaming document batches. Recent well-known model-based text stream clustering models, such as: DTM, DCT, MStream, etc. are considered as word-indep

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Da San Martino, Giovanni, Alessandro Sperduti, Fabio Aiolli, and Alessandro Moschitti. "Efficient Online Learning for Mapping Kernels on Linguistic Structures." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3421–28. http://dx.doi.org/10.1609/aaai.v33i01.33013421.

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Kernel methods are popular and effective techniques for learning on structured data, such as trees and graphs. One of their major drawbacks is the computational cost related to making a prediction on an example, which manifests in the classification phase for batch kernel methods, and especially in online learning algorithms. In this paper, we analyze how to speed up the prediction when the kernel function is an instance of the Mapping Kernels, a general framework for specifying kernels for structured data which extends the popular convolution kernel framework. We theoretically study the gener

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Luo, Haoran, Haihong E, Yuhao Yang, et al. "NQE: N-ary Query Embedding for Complex Query Answering over Hyper-Relational Knowledge Graphs." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 4 (2023): 4543–51. http://dx.doi.org/10.1609/aaai.v37i4.25576.

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Complex query answering (CQA) is an essential task for multi-hop and logical reasoning on knowledge graphs (KGs). Currently, most approaches are limited to queries among binary relational facts and pay less attention to n-ary facts (n≥2) containing more than two entities, which are more prevalent in the real world. Moreover, previous CQA methods can only make predictions for a few given types of queries and cannot be flexibly extended to more complex logical queries, which significantly limits their applications. To overcome these challenges, in this work, we propose a novel N-ary Query Embedd

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Auerbach, Joshua, David F. Bacon, Rachid Guerraoui, Jesper Honig Spring, and Jan Vitek. "Flexible task graphs." ACM SIGPLAN Notices 43, no. 7 (2008): 1–11. http://dx.doi.org/10.1145/1379023.1375659.

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Dissertations / Theses on the topic "Batches of task graphs"

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Toch, Lamiel. "Contributions aux techniques d’ordonnancement sur plates-formes parallèles ou distribuées." Electronic Thesis or Diss., Besançon, 2012. http://www.theses.fr/2012BESA2045.

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Les travaux présentés dans ce document portent sur l'ordonnancement d'applications parallèles sur des plates-formes parallèles (cluster) ou distribuées (grilles de calcul). Dans nos travaux de recherche nous nous sommes concentrés sur l'ordonnancement d'applications modélisées par un DAG, graphe orienté sans cycle, pour les grilles de calcul et sur l'ordonnancement pour les (cluster, machines multiprocesseurs) de programmes parallèles (jobs parallèles) représentés sous la forme de surface rectangulaire dont les deux dimensions sont le nombre de processeurs requis et la durée d'exécution. Les r

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Dechu, Satish. "Task graphs mapping on to network processors using simulated annealing /." Available to subscribers only, 2007. http://proquest.umi.com/pqdweb?did=1453188941&sid=15&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Negelspach, Greg L. "Grain size management in repetitive task graphs for multiprocessor computer scheduling." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA288575.

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Chieregato, Federico. "Modelling task execution time in Directed Acyclic Graphs for efficient distributed management." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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In this thesis, has been shown a framework that predicts the execution time of tasks in Directed Acyclic Graphs (DAG), each task is the smallest unit of work that executes a function over a set of inputs and in this scenario represents a vertex in a DAG. This thesis includes an implementation for extracting profiling information from Apache Spark, as well, an evaluation of the framework for the Spark decision support benchmark TPC-DS and an in-house and completely different DAG runtime system for real-world DAGS, involving computational quantum chemistry applications. Speeding up the execu

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Witt, Carl Philipp. "Predictive Resource Management for Scientific Workflows." Doctoral thesis, Humboldt-Universität zu Berlin, 2020. http://dx.doi.org/10.18452/21608.

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Um Erkenntnisse aus großen Mengen wissenschaftlicher Rohdaten zu gewinnen, sind komplexe Datenanalysen erforderlich. Scientific Workflows sind ein Ansatz zur Umsetzung solcher Datenanalysen. Um Skalierbarkeit zu erreichen, setzen die meisten Workflow-Management-Systeme auf bereits existierende Lösungen zur Verwaltung verteilter Ressourcen, etwa Batch-Scheduling-Systeme. Die Abschätzung der Ressourcen, die zur Ausführung einzelner Arbeitsschritte benötigt werden, wird dabei immer noch an die Nutzer:innen delegiert. Dies schränkt die Leistung und Benutzerfreundlichkeit von Workflow-Management-S

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Kasinger, Charles D. "A periodic scheduling heuristic for mapping iterative task graphs onto distributed memory multiprocessors." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA286047.

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Koman, Charles Brian. "A tool for efficient execution and development of repetitive task graphs on a distributed memory multiprocessor." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1995. http://handle.dtic.mil/100.2/ADA305995.

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Pop, Ruxandra. "Mapping Concurrent Applications to Multiprocessor Systems with Multithreaded Processors and Network on Chip-Based Interconnections." Licentiate thesis, Linköpings universitet, Institutionen för datavetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-64256.

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Network on Chip (NoC) architectures provide scalable platforms for designing Systems on Chip (SoC) with large number of cores. Developing products and applications using an NoC architecture offers many challenges and opportunities. A tool which can map an application or a set of applications to a given NoC architecture will be essential. In this thesis we first survey current techniques and we present our proposals for mapping and scheduling of concurrent applications to NoCs with multithreaded processors as computational resources. NoC platforms are basically a special class of Multiprocessor

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Gurhem, Jérôme. "Paradigmes de programmation répartie et parallèle utilisant des graphes de tâches pour supercalculateurs post-pétascale." Thesis, Lille, 2021. http://www.theses.fr/2021LILUI005.

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Depuis le milieu des années 1990, les bibliothèques de transmission de messages sont les technologies les plus utilisées pour développer des applications parallèles et distribuées. Des modèles de programmation basés sur des tâches peuvent être utilisés, par exemple, pour éviter les communications collectives sur toutes les ressources comme les réductions, les diffusions ou les rassemblements en les transformant en multiples opérations avec des tâches. Ensuite, ces opérations peuvent être planifiées par l'ordonnanceur pour placer les données et les calculs de manière à optimiser et réduire les

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Bouguelia, Sara. "Modèles de dialogue et reconnaissance d'intentions composites dans les conversations Utilisateur-Chatbot orientées tâches." Electronic Thesis or Diss., Lyon 1, 2023. http://www.theses.fr/2023LYO10106.

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Les Systèmes de Dialogue (ou simplement chatbots) sont très demandés de nos jours. Ils permettent de comprendre les besoins des utilisateurs (ou intentions des utilisateurs), exprimés en langage naturel, et de répondre à ces intentions en invoquant les APIs (Interfaces de Programmation d’Application) appropriées. Les chatbots sont connus pour leur interface facile à utiliser et ils ne nécessitent que l'une des capacités les plus innées des humains qui est l'utilisation du langage naturel. L'amélioration continue de l'Intelligence Artificielle (IA), du Traitement du Langage Naturel (NLP) et du

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Books on the topic "Batches of task graphs"

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Shukla, Shridhar B. Real-time execution control of task-level data-flow graphs using a compile-time approach. Naval Postgraduate School, 1992.

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Brooks, Colton. Ielts Writing Task 1 - Data, Charts, Graphs and Letters. Lulu Press, Inc., 2015.

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Worthwhile IELTS Writing TASK-1: GRAPHS,TABLES,DIAGRAMS,CHARTS &FIGURES. Rana Books India, 2021.

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Brooks, Colton. Ielts Writing Task 1 - Data, Charts, Graphs and Letters - Fill the Gap. Lulu Press, Inc., 2015.

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HOSSAIN, Delwer. IELTS GRAPH : 200 Samples from Past Exam : IELTS ACADEMIC WRITING TASK 1: 200 Practice Test with Answer, Bar and Line Graphs, Pie Charts, Maps and Tables. Independently Published, 2021.

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HOSSAIN, Delwer. IELTS GRAPH : 200 Samples from Past Exam : IELTS ACADEMIC WRITING TASK 1: 200 Practice Test with Answer, Bar and Line Graphs, Pie Charts, Maps and Tables. Independently Published, 2021.

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HOSSAIN, Delwer. IELTS GRAPH : 200 Samples from Past Exam : IELTS ACADEMIC WRITING TASK 1: 200 Practice Test with Answer, Bar and Line Graphs, Pie Charts, Maps and Tables. Independently Published, 2021.

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Consultants, Ielts Writing, and Marc Roche. IELTS Writing Masterclass 8. 5. Master IELTS Writing Academic + General Task 1 and 2, Including Graphs, Letters, Essay Writing and Grammar for IELTS Academic and General Training: IELTS Writing Originals ©. Independently Published, 2020.

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Consultants, Ielts Writing, and Marc Roche. IELTS Writing Masterclass 8. 5. Master IELTS Writing Academic + General Task 1 and 2, Including Graphs, Letters, Essay Writing and Grammar for IELTS Academic and General Training: IELTS Writing Originals ©. Independently Published, 2021.

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Little, Danity. How Women Executives Succeed. Greenwood Publishing Group, Inc., 1994. http://dx.doi.org/10.5040/9798400667008.

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The significance of this study on women executives is twofold: one, the book is about women in the public sector, and two, it is written by a woman in the executive service of the government itself. The treatise is a well-documented study of seventy-eight women executives who advanced into the upper reaches of the government executive service. The work analyzes the significant experiences, individuals, developmental stages, and barriers that these women encountered. It provides constructive information for women employees, women managers, and managers of women and minorities. The introductory

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Book chapters on the topic "Batches of task graphs"

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Diakité, Sékou, Loris Marchal, Jean-Marc Nicod, and Laurent Philippe. "Steady-State for Batches of Identical Task Trees." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03869-3_22.

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Eberhart, Aaron, Cogan Shimizu, Christopher Stevens, Pascal Hitzler, Christopher W. Myers, and Benji Maruyama. "A Domain Ontology for Task Instructions." In Knowledge Graphs and Semantic Web. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65384-2_1.

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Brézillon, Patrick. "Task-Realization Models in Contextual Graphs." In Modeling and Using Context. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11508373_5.

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Finta, Lucian, and Zhen Liu. "Makespan minimization of task graphs with random task running times." In DIMACS Series in Discrete Mathematics and Theoretical Computer Science. American Mathematical Society, 1995. http://dx.doi.org/10.1090/dimacs/021/10.

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Miranda-Jiménez, Sabino, Alexander Gelbukh, and Grigori Sidorov. "Summarizing Conceptual Graphs for Automatic Summarization Task." In Conceptual Structures for STEM Research and Education. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35786-2_18.

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Boeres, Cristina, Aline Nascimento⋆, and Vinod E. F. Rebello. "Scheduling Arbitrary Task Graphs on LogP Machines." In Euro-Par’99 Parallel Processing. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48311-x_44.

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Klijn, Eva L., Felix Mannhardt, and Dirk Fahland. "Aggregating Event Knowledge Graphs for Task Analysis." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27815-0_36.

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AbstractAggregation of event data is a key operation in process mining for revealing behavioral features of processes for analysis. It has primarily been studied over sequences of events in event logs. The data model of event knowledge graphs enables new analysis questions requiring new forms of aggregation. We focus on analyzing task executions in event knowledge graphs. We show that existing aggregation operations are inadequate and propose new aggregation operations, formulated as query operators over labeled property graphs. We show on the BPIC’17 dataset that the new aggregation operations allow gaining new insights into differences in task executions, actor behavior, and work division.

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Baskiyar, Sanjeev, and Christopher Dickinson. "Scheduling Directed A-Cyclic Task Graphs on Heterogeneous Processors Using Task Duplication." In High Performance Computing - HiPC 2003. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-24596-4_28.

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Gelenbe, Erol. "Critical Path Length of Large Acyclic Task Graphs." In Parallel Computing on Distributed Memory Multiprocessors. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-58066-6_11.

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Löwe, Welf, Wolf Zimmermann, Sven Dickert, and Jörn Eisenbiegler. "Source Code and Task Graphs in Program Optimization." In High-Performance Computing and Networking. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-48228-8_28.

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Conference papers on the topic "Batches of task graphs"

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Zhu, Wenhao, Tianyu Wen, Guojie Song, Xiaojun Ma, and Liang Wang. "Hierarchical Transformer for Scalable Graph Learning." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/523.

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Graph Transformer is gaining increasing attention in the field of machine learning and has demonstrated state-of-the-art performance on benchmarks for graph representation learning. However, as current implementations of Graph Transformer primarily focus on learning representations of small-scale graphs, the quadratic complexity of the global self-attention mechanism presents a challenge for full-batch training when applied to larger graphs. Additionally, conventional sampling-based methods fail to capture necessary high-level contextual information, resulting in a significant loss of performa

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Auerbach, Joshua, David F. Bacon, Rachid Guerraoui, Jesper Honig Spring, and Jan Vitek. "Flexible task graphs." In the 2008 ACM SIGPLAN-SIGBED conference. ACM Press, 2008. http://dx.doi.org/10.1145/1375657.1375659.

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Yang, Zhen, Tinglin Huang, Ming Ding, et al. "BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs." In KDD '23: The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 2023. http://dx.doi.org/10.1145/3580305.3599263.

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Li, Jinqing, Xiaojun Chen, Dakui Wang, and Yuwei Li. "Enhancing Label Representations with Relational Inductive Bias Constraint for Fine-Grained Entity Typing." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/529.

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Fine-Grained Entity Typing (FGET) is a task that aims at classifying an entity mention into a wide range of entity label types. Recent researches improve the task performance by imposing the label-relational inductive bias based on the hierarchy of labels or label co-occurrence graph. However, they usually overlook explicit interactions between instances and labels which may limit the capability of label representations. Therefore, we propose a novel method based on a two-phase graph network for the FGET task to enhance the label representations, via imposing the relational inductive biases of

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Agrawal, Kunal, Charles E. Leiserson, and Jim Sukha. "Executing task graphs using work-stealing." In 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS). IEEE, 2010. http://dx.doi.org/10.1109/ipdps.2010.5470403.

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Long, Douglas L., and Lori A. Clarke. "Task interaction graphs for concurrency analysis." In the 11th international conference. ACM Press, 1989. http://dx.doi.org/10.1145/74587.74592.

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Carpov, Sergiu, Jacques Carlier, Dritan Nace, and Renaud Sirdey. "Probabilistic Parameters of Conditional Task Graphs." In 2011 14th International Conference on Network-Based Information Systems (NBiS). IEEE, 2011. http://dx.doi.org/10.1109/nbis.2011.63.

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Szymanek, Radoslaw, and Krzysztof Krzysztof. "Partial task assignment of task graphs under heterogeneous resource constraints." In the 40th conference. ACM Press, 2003. http://dx.doi.org/10.1145/775832.775895.

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Dokulil, Jiri, and Jana Katreniakova. "Visualization of Open Community Runtime Task Graphs." In 2017 21st International Conference on Information Visualisation (IV). IEEE, 2017. http://dx.doi.org/10.1109/iv.2017.31.

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Sbîrlea, Dragos, Zoran Budimlić, and Vivek Sarkar. "Bounded memory scheduling of dynamic task graphs." In the 23rd international conference. ACM Press, 2014. http://dx.doi.org/10.1145/2628071.2628090.

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Reports on the topic "Batches of task graphs"

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Mbabzi, Kikundwa Emma. Standardisation of Staff Training to Increase Efficiency. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317427.

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In any industry or organization, personnel training is emphasized with reference to National Regulatory Authorities (NRAs) guidelines and other globally accepted guidelines. In spite of many refresher training programs, the pharmaceutical industry still faces significant variations in individual/ team efficiency and productivity. Individuals/teams given the same task, SOPs, environment and materials continue to produce significantly different results reflecting the possibility of operating on different sets of theoretical and practical information, which may stem from differing trainer, traini

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Küsters, Ralf, and Ralf Molitor. Computing Most Specific Concepts in Description Logics with Existential Restrictions. Aachen University of Technology, 2000. http://dx.doi.org/10.25368/2022.108.

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Computing the most specific concept (msc) is an inference task that can be used to support the 'bottom-up' construction of knowledge bases for KR systems based on description logics. For description logics that allow for number restrictions or existential restrictions, the msc need not exist, though. Previous work on this problem has concentrated on description logics that allow for universal value restrictions and number restrictions, but not for existential restrictions. The main new contribution of this paper is the treatment of description logics with existential restrictions. More precise

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Kriegel, Francesco. Terminological knowledge aquisition in probalistic description logic. Technische Universität Dresden, 2018. http://dx.doi.org/10.25368/2022.239.

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For a probabilistic extension of the description logic EL⊥, we consider the task of automatic acquisition of terminological knowledge from a given probabilistic interpretation. Basically, such a probabilistic interpretation is a family of directed graphs the vertices and edges of which are labeled, and where a discrete probabilitymeasure on this graph family is present. The goal is to derive so-called concept inclusions which are expressible in the considered probabilistic description logic and which hold true in the given probabilistic interpretation. A procedure for an appropriate axiomatiza

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