Takip et
Yoonho Boo
Yoonho Boo
Rebellions Inc.
rebellions.ai üzerinde doğrulanmış e-posta adresine sahip
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
Fully neural network based speech recognition on mobile and embedded devices
J Park, Y Boo, I Choi, S Shin, W Sung
Advances in neural information processing systems 31, 2018
482018
SVD-softmax: Fast softmax approximation on large vocabulary neural networks
K Shim, M Lee, I Choi, Y Boo, W Sung
Advances in neural information processing systems 30, 2017
472017
Fixed-point optimization of deep neural networks with adaptive step size retraining
S Shin, Y Boo, W Sung
2017 IEEE International conference on acoustics, speech and signal …, 2017
452017
Structured sparse ternary weight coding of deep neural networks for efficient hardware implementations
Y Boo, W Sung
2017 IEEE international workshop on signal processing systems (SIPS), 1-6, 2017
412017
Stochastic precision ensemble: self-knowledge distillation for quantized deep neural networks
Y Boo, S Shin, J Choi, W Sung
Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 6794-6802, 2021
232021
Knowledge distillation for optimization of quantized deep neural networks
S Shin, Y Boo, W Sung
2020 IEEE Workshop on Signal Processing Systems (SiPS), 1-6, 2020
19*2020
Fixed-point optimization of transformer neural network
Y Boo, W Sung
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
152020
Quantized neural networks: Characterization and holistic optimization
Y Boo, S Shin, W Sung
2020 IEEE Workshop on Signal Processing Systems (SiPS), 1-6, 2020
122020
Memorization capacity of deep neural networks under parameter quantization
Y Boo, S Shin, W Sung
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
92019
Hlhlp: Quantized neural networks training for reaching flat minima in loss surface
S Shin, J Park, Y Boo, W Sung
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5784-5791, 2020
62020
Sqwa: Stochastic quantized weight averaging for improving the generalization capability of low-precision deep neural networks
S Shin, Y Boo, W Sung
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
42021
LightTrader: World’s first AI-enabled High-Frequency Trading Solution with 16 TFLOPS/64 TOPS Deep Learning Inference Accelerators
H Kim, S Yoo, J Bae, K Bong, Y Boo, K Charfi, HE Kim, HS Kim, J Kim, ...
2022 IEEE Hot Chips 34 Symposium (HCS), 1-10, 2022
12022
Hierarchical Recurrent Neural Networks for Acoustic Modeling.
J Park, I Choi, Y Boo, W Sung
INTERSPEECH, 3728-3732, 2018
12018
2.4 ATOMUS: A 5nm 32TFLOPS/128TOPS ML System-on-Chip for Latency Critical Applications
CH Yu, HE Kim, S Shin, K Bong, H Kim, Y Boo, J Bae, M Kwon, K Charfi, ...
2024 IEEE International Solid-State Circuits Conference (ISSCC) 67, 42-44, 2024
2024
Neural network training method and apparatus
S Shin, S Wonyong, BOO Yoonho
US Patent App. 17/526,221, 2022
2022
Characterization and Optimization of Quantized Deep Neural Networks
부윤호
서울대학교 대학원, 2020
2020
Compression of Deep Neural Networks with Structured Sparse Ternary Coding
Y Boo, W Sung
Journal of Signal Processing Systems 91, 1009-1019, 2019
2019
On-Device End-to-end Speech Recognition with Multi-Step Parallel Rnns
Y Boo, J Park, L Lee, W Sung
2018 IEEE Spoken Language Technology Workshop (SLT), 376-381, 2018
2018
Capacity of Deep Neural Networks under Parameter Quantization
Y Boo, S Shin, W Sung
2018
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