Digital Library
Search: "[ keyword: Scaling ]" (12)
Determining the number of Clusters in On-Line Document Clustering Algorithm
Tae Chang Jee , Hyun Jin Lee , Yill Byung Lee The KIPS Transactions:PartB ,
Vol. 14, No. 7, pp. 513-522,
Dec.
2007
10.3745/KIPSTB.2007.14.7.513
10.3745/KIPSTB.2007.14.7.513
Computer Graphics & Auto Setup Method of Best Expression Transfer Path at the Space of Facial Expressions
Sung Ho Kim The KIPS Transactions:PartA,
Vol. 14, No. 2, pp. 85-90,
Apr.
2007
10.3745/KIPSTA.2007.14.2.85
10.3745/KIPSTA.2007.14.2.85
The Development of an Automatic Tool for Formal Concept Analysis and its Applications on Medical Domain
Hong Gee Kim , Yu Kyung Kang , Suk Hyung Hwang , Dong Soon Kim The KIPS Transactions:PartD,
Vol. 13, No. 7, pp. 997-1008,
Dec.
2006
10.3745/KIPSTD.2006.13.7.997
10.3745/KIPSTD.2006.13.7.997
Imbalanced Data Improvement Techniques Based on SMOTE and Light GBM
Young-Jin Han, In-Whee Joe KIPS Transactions on Computer and Communication Systems,
Vol. 11, No. 12, pp. 445-452,
Dec.
2022
https://doi.org/10.3745/KTCCS.2022.11.12.445
Keywords: Machine Learning, Scaling, SMOTE, Light GBM, Imbalanced Classification
https://doi.org/10.3745/KTCCS.2022.11.12.445
Keywords: Machine Learning, Scaling, SMOTE, Light GBM, Imbalanced Classification
Transfer Learning Technique for Accelerating Learning of Reinforcement Learning-Based Horizontal Pod Autoscaling Policy
Yonghyeon Jang, Heonchang Yu, SungSuk Kim KIPS Transactions on Computer and Communication Systems,
Vol. 11, No. 4, pp. 105-112,
Apr.
2022
https://doi.org/10.3745/KTCCS.2022.11.4.105
Keywords: Kubernetes, Reinforcement Learning, Autoscaling
https://doi.org/10.3745/KTCCS.2022.11.4.105
Keywords: Kubernetes, Reinforcement Learning, Autoscaling
Constant Time Algorithms for Region Expansion and Scaling of Linear Quadtrees on RMESH
Jin Woon Woo The KIPS Transactions:PartA,
Vol. 11, No. 3, pp. 173-180,
Jun.
2004
10.3745/KIPSTA.2004.11.3.173
10.3745/KIPSTA.2004.11.3.173
An Improvement of Kubernetes Auto-Scaling Based on Multivariate Time Series Analysis
Yong Hae Kim, Young Han Kim KIPS Transactions on Computer and Communication Systems,
Vol. 11, No. 3, pp. 73-82,
Mar.
2022
https://doi.org/10.3745/KTCCS.2022.11.3.73
Keywords: Multivariate Time Series, VAR, Kubernetes, Auto-Scaling
https://doi.org/10.3745/KTCCS.2022.11.3.73
Keywords: Multivariate Time Series, VAR, Kubernetes, Auto-Scaling
An Online Scaling Method for Improving the Availability of a Database Cluster
Lee Chung Ho , Jang Yong Il , Bae Hae Yeong The KIPS Transactions:PartD,
Vol. 10, No. 6, pp. 935-948,
Oct.
2003
10.3745/KIPSTD.2003.10.6.935
10.3745/KIPSTD.2003.10.6.935
Online Reorganization of B+ tree in a Scalable and Highly Available Database Cluster
Chung Ho Lee , Hea Young Bae The KIPS Transactions:PartD,
Vol. 9, No. 5, pp. 801-812,
Oct.
2002
10.3745/KIPSTD.2002.9.5.801
10.3745/KIPSTD.2002.9.5.801
The Optimization Mechanism of CPU/GPU Computing Resource for Minimization of Performance Interference and Calculation Efficiency in Volunteer Computing Environment
Bong Woo Bak, Chung Geon Song, Heon Chang Yu KIPS Transactions on Computer and Communication Systems,
Vol. 6, No. 12, pp. 479-486,
Dec.
2017
10.3745/KTCCS.2017.6.12.479
Keywords: Volunteer Computing, resource management, Task Scaling
10.3745/KTCCS.2017.6.12.479
Keywords: Volunteer Computing, resource management, Task Scaling