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Showing results 1 to 8 of 8

1
An Energy-Efficient Sparse Deep-Neural-Network Learning Accelerator with Fine-Grained Mixed Precision of FP8–FP16

Lee,Jinsu; LEE, JUHYOUNG; Han, Donghyeon; Lee, Jinmook; Park, Gwangtae; Yoo, Hoi-Jun, IEEE Solid-State Circuits Letters, v.2, no.11, pp.232 - 235, 2019-11

2
Design of Processing-in-Memory With Triple Computational Path and Sparsity Handling for Energy-Efficient DNN Training

Han, Wontak; Heo, Jaehoon; Kim, Junsoo; Lim, Sukbin; Kim, Joo-Young, IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS, v.12, no.2, pp.354 - 366, 2022-06

3
Development of an integrated evaluation model of technical and non-technical skills for nuclear power plant operation teams = 원자력 발전소 운전팀의 기술적/비기술적 기량의 종합적 평가모형 개발link

Yim, Ho-Bin; 임호빈; et al, 한국과학기술원, 2014

4
Neuro-control of Seismically Excited Steel Structure through Sensitivity Evaluation Scheme

Kim, Dong-Hyawn; Lee, In Won, EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, v.30, no.9, pp.1361 - 1378, 2001-09

5
Outsourcing frontline functions and implications on customer-oriented behaviors: A case of a telecommunications company and its partners in South Korea

Song, ChanHoo; Lee, Sunhee; Lee, EueHun, JOURNAL OF MANAGEMENT & ORGANIZATION, v.19, no.2, pp.210 - 223, 2013-03

6
Seed growing for interactive image segmentation using SVM classification with geodesic distance

Park, Sun Jeong; Lee, Han Sang; Kim, Junmo, ELECTRONICS LETTERS, v.53, no.1, pp.22 - 23, 2017-01

7
T-PIM: An Energy-Efficient Processing-in-Memory Accelerator for End-to-End On-Device Training

Heo, Jaehoon; Kim, Junsoo; Lim, Sukbin; Han, Wontak; Kim, Joo-Young, IEEE JOURNAL OF SOLID-STATE CIRCUITS, v.58, no.3, pp.600 - 613, 2023-03

8
Understanding the Implication of Non-Volatile Memory for Large-Scale Graph Neural Network Training

Lee, Yunjae; Kwon, Youngeun; Rhu, Minsoo, IEEE COMPUTER ARCHITECTURE LETTERS, v.20, no.2, pp.118 - 121, 2021-07

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