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Relevant bibliographies by topics / Batch update

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Journal articles

Academic literature on the topic 'Batch update'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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Journal articles on the topic "Batch update"

1

Pereira, Fabio Henrique, Francisco Elânio Bezerra, Diego Oliva, et al. "Forecast Model Update Based on a Real-Time Data Processing Lambda Architecture for Estimating Partial Discharges in Hydrogenerator." Sensors 20, no. 24 (2020): 7242. http://dx.doi.org/10.3390/s20247242.

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The prediction of partial discharges in hydrogenerators depends on data collected by sensors and prediction models based on artificial intelligence. However, forecasting models are trained with a set of historical data that is not automatically updated due to the high cost to collect sensors’ data and insufficient real-time data analysis. This article proposes a method to update the forecasting model, aiming to improve its accuracy. The method is based on a distributed data platform with the lambda architecture, which combines real-time and batch processing techniques. The results show that th

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2

Cunha, João, Rui Serra, Nuno Lau, Luís Seabra Lopes, and Antóio J. R. Neves. "Batch Reinforcement Learning for Robotic Soccer Using the Q-Batch Update-Rule." Journal of Intelligent & Robotic Systems 80, no. 3-4 (2015): 385–99. http://dx.doi.org/10.1007/s10846-014-0171-1.

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3

Yang, Zhuang, Cheng Wang, Yu Zang, and Jonathan Li. "Mini-batch algorithms with Barzilai–Borwein update step." Neurocomputing 314 (November 2018): 177–85. http://dx.doi.org/10.1016/j.neucom.2018.06.002.

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4

Lambert, Sherwood Lane. "Auto Accessories, Inc.: An Educational Case on Online Transaction Processing (OLTP) and Controls as Compared to Batch Processing and Controls." Journal of Emerging Technologies in Accounting 14, no. 2 (2017): 59–81. http://dx.doi.org/10.2308/jeta-51844.

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ABSTRACT The intent of this educational case is to increase students' understanding of online transaction processing (OLTP) and controls as compared to batch processing and controls. Learning concepts about batch processing is important because many entities continue to use batch processing for critical applications such as payroll, credit card processing, and Big Data. Students learn the advantages and disadvantages of batch processing and OLTP. The case provides a Microsoft Access database that includes a working batch program (module) and an online screen (form). Students use the form to up

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Brown, Christopher C., and Erin Elzi. "Revisiting the cataloging of free Internet resources at the University of Denver." Interlending & Document Supply 44, no. 1 (2016): 31–36. http://dx.doi.org/10.1108/ilds-11-2015-0034.

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Purpose – This paper aims to present updated statistics demonstrating the value of cataloging free Internet resources and the challenges of batch loading, vendor records, electronic resource modules and discovery tools, as an update to the 2008 paper in this journal Design/methodology/approach – Updates the statistics from the URL redirection system for tracking user access to freely available Web publications. Findings – With more projects and bibliographic records included within the scope of the project, users still find and use the links to outbound content. New technologies and management

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6

Foerster, Klaus-Tycho, Janne H. Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. "Input-Dynamic Distributed Algorithms for Communication Networks." Proceedings of the ACM on Measurement and Analysis of Computing Systems 5, no. 1 (2021): 1–33. http://dx.doi.org/10.1145/3447384.

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Consider a distributed task where the communication network is fixed but the local inputs given to the nodes of the distributed system may change over time. In this work, we explore the following question: if some of the local inputs change, can an existing solution be updated efficiently, in a dynamic and distributed manner? To address this question, we define the batch dynamic \congest model in which we are given a bandwidth-limited communication network and a dynamic edge labelling defines the problem input. The task is to maintain a solution to a graph problem on the labeled graph under ba

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7

Dangi, Siddharth, Suraj Gowda, Helene G. Moorman, et al. "Continuous Closed-Loop Decoder Adaptation with a Recursive Maximum Likelihood Algorithm Allows for Rapid Performance Acquisition in Brain-Machine Interfaces." Neural Computation 26, no. 9 (2014): 1811–39. http://dx.doi.org/10.1162/neco_a_00632.

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Closed-loop decoder adaptation (CLDA) is an emerging paradigm for both improving and maintaining online performance in brain-machine interfaces (BMIs). The time required for initial decoder training and any subsequent decoder recalibrations could be potentially reduced by performing continuous adaptation, in which decoder parameters are updated at every time step during these procedures, rather than waiting to update the decoder at periodic intervals in a more batch-based process. Here, we present recursive maximum likelihood (RML), a CLDA algorithm that performs continuous adaptation of a Kal

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Huang, Siyuan, Brian D. Hoskins, Matthew W. Daniels, Mark D. Stiles, and Gina C. Adam. "Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 10 (2020): 13813–14. http://dx.doi.org/10.1609/aaai.v34i10.7178.

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Faster and more energy efficient hardware accelerators are critical for machine learning on very large datasets. The energy cost of performing vector-matrix multiplication and repeatedly moving neural network models in and out of memory motivates a search for alternative hardware and algorithms. We propose to use streaming batch principal component analysis (SBPCA) to compress batch data during training by using a rank-k approximation of the total batch update. This approach yields comparable training performance to minibatch gradient descent (MBGD) at the same batch size while reducing overal

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Gineste, Michael, and Jo Eidsvik. "Batch seismic inversion using the iterative ensemble Kalman smoother." Computational Geosciences 25, no. 3 (2021): 1105–21. http://dx.doi.org/10.1007/s10596-021-10043-4.

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AbstractAn ensemble-based method for seismic inversion to estimate elastic attributes is considered, namely the iterative ensemble Kalman smoother. The main focus of this work is the challenge associated with ensemble-based inversion of seismic waveform data. The amount of seismic data is large and, depending on ensemble size, it cannot be processed in a single batch. Instead a solution strategy of partitioning the data recordings in time windows and processing these sequentially is suggested. This work demonstrates how this partitioning can be done adaptively, with a focus on reliable and eff

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10

Ye, Yongqiang, and Danwei Wang. "Implementation of ILC batch update using a robotic experimental setup." Microprocessors and Microsystems 30, no. 5 (2006): 259–67. http://dx.doi.org/10.1016/j.micpro.2005.11.003.

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