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Young Jin Kim
Young Jin Kim
Microsoft, Georgia Tech. (CSE)
Dirección de correo verificada de gatech.edu - Página principal
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Prediction of weather-induced airline delays based on machine learning algorithms
S Choi, YJ Kim, S Briceno, D Mavris
Digital Avionics Systems Conference (DASC), 2016 IEEE/AIAA 35th, 2016
2002016
A deep learning approach to flight delay prediction
YJ Kim, S Choi, S Briceno, D Mavris
2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC), 2016
189*2016
How good are gpt models at machine translation? a comprehensive evaluation
A Hendy, M Abdelrehim, A Sharaf, V Raunak, M Gabr, H Matsushita, ...
arXiv preprint arXiv:2302.09210, 2023
1502023
Lower numerical precision deep learning inference and training
A Rodriguez, E Segal, E Meiri, E Fomenko, YJ Kim, H Shen, B Ziv
https://software.intel.com/en-us/articles/lower-numerical-precision-deep …, 2018
692018
Taming sparsely activated transformer with stochastic experts
S Zuo, X Liu, J Jiao, YJ Kim, H Hassan, R Zhang, T Zhao, J Gao
arXiv preprint arXiv:2110.04260, 2021
652021
From Research to Production and Back: Ludicrously Fast Neural Machine Translation
YJ Kim, M Junczys-Dowmunt, H Hassan, AF Aji, K Heafield, ...
Proceedings of the 3rd Workshop on Neural Generation and Translation, 280-288, 2019
622019
Scalable and efficient moe training for multitask multilingual models
YJ Kim, AA Awan, A Muzio, AFC Salinas, L Lu, A Hendy, S Rajbhandari, ...
arXiv preprint arXiv:2109.10465, 2021
522021
FastFormers: Highly efficient transformer models for natural language understanding
YJ Kim, HH Awadalla
arXiv preprint arXiv:2010.13382, 2020
462020
Artificial neural network models for airport capacity prediction
S Choi, YJ Kim
Journal of Air Transport Management 97, 102146, 2021
342021
Cost-sensitive prediction of airline delays using machine learning
S Choi, YJ Kim, S Briceno, D Mavris
2017 IEEE/AIAA 36th Digital Avionics Systems, 2017
192017
A paradigm shift in machine translation: Boosting translation performance of large language models
H Xu, YJ Kim, A Sharaf, HH Awadalla
arXiv preprint arXiv:2309.11674, 2023
182023
Gating dropout: Communication-efficient regularization for sparsely activated transformers
R Liu, YJ Kim, A Muzio, H Hassan
International Conference on Machine Learning, 13782-13792, 2022
122022
Parallel Simulation of Agent-Based Model for Air Traffic Network
YJ Kim, OJ Pinon-Fischer, DN Mavris
AIAA Modeling and Simulation Technologies Conference, 2799, 2015
72015
Time-and space-parallel simulation of air traffic networks
YJ Kim, D Mavris, R Fujimoto
Simulation 95 (12), 1213-1228, 2019
62019
Finequant: Unlocking efficiency with fine-grained weight-only quantization for llms
YJ Kim, R Henry, R Fahim, HH Awadalla
arXiv preprint arXiv:2308.09723, 2023
52023
Who Says Elephants Can't Run: Bringing Large Scale MoE Models into Cloud Scale Production
YJ Kim, R Henry, R Fahim, HH Awadalla
arXiv preprint arXiv:2211.10017, 2022
42022
Accelerating TensorFlow on Modern Intel Architectures
E Ould-Ahmed-Vall, M Abuzaina, MF Amin, J Bobba, RS Dubtsov, ...
International workshop on architectures for intelligent machines, 2017
42017
Mixture of Quantized Experts (MoQE): Complementary Effect of Low-bit Quantization and Robustness
YJ Kim, R Fahim, HH Awadalla
arXiv preprint arXiv:2310.02410, 2023
22023
AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers
G Jawahar, S Mukherjee, X Liu, YJ Kim, M Abdul-Mageed, ...
arXiv preprint arXiv:2210.07535, 2022
22022
A deep learning and parallel simulation methodology for air traffic management.
YJ Kim
Georgia Institute of Technology, Atlanta, GA, USA, 2018
22018
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Artículos 1–20