| Efficient Mitchell’s approximate log multipliers for convolutional neural networks MS Kim, AA Del Barrio, LT Oliveira, R Hermida, N Bagherzadeh IEEE Transactions on Computers 68 (5), 660-675, 2018 | 126 | 2018 |
| The effects of approximate multiplication on convolutional neural networks MS Kim, AA Del Barrio, H Kim, N Bagherzadeh IEEE Transactions on Emerging Topics in Computing 10 (2), 904-916, 2021 | 73 | 2021 |
| Low-power implementation of Mitchell's approximate logarithmic multiplication for convolutional neural networks MS Kim, AA Del Barrio, R Hermida, N Bagherzadeh 2018 23rd Asia and South Pacific design automation conference (ASP-DAC), 617-622, 2018 | 56 | 2018 |
| Cost-effective, energy-efficient, and scalable storage computing for large-scale AI applications J Do, VC Ferreira, H Bobarshad, M Torabzadehkashi, S Rezaei, ... ACM Transactions on Storage (TOS) 16 (4), 1-37, 2020 | 50 | 2020 |
| PLAM: A posit logarithm-approximate multiplier R Murillo, AA Del Barrio, G Botella, MS Kim, HJ Kim, N Bagherzadeh IEEE Transactions on Emerging Topics in Computing 10 (4), 2079-2085, 2021 | 39 | 2021 |
| A cost-efficient iterative truncated logarithmic multiplication for convolutional neural networks HJ Kim, MS Kim, AA Del Barrio, N Bagherzadeh 2019 IEEE 26th symposium on computer arithmetic (ARITH), 108-111, 2019 | 34 | 2019 |
| Design of Power-Efficient FPGA Convolutional Cores with Approximate Log Multiplier. LT Oliveira, MS Kim, AADB García, N Bagherzadeh, R Menotti ESANN, 2019 | 9 | 2019 |
| PLAM: A Posit Logarithm-Approximate Multiplier for Power Efficient Posit-based DNNs R Murillo, AAD Barrio, G Botella, MS Kim, H Kim, N Bagherzadeh arXiv Computer Science, Machine Learning (Feb 2021), 2021 | 2 | 2021 |
| Cost-Efficient Approximate Log Multipliers for Convolutional Neural Networks MS Kim University of California, Irvine, 2020 | | 2020 |
