Min Soo Kim

According to our database, Min Soo Kim authored at least 8 papers between 2018 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

PLAM: A Posit Logarithm-Approximate Multiplier.

Raul Murillo, Alberto A. Del Barrio, Guillermo Botella, Min Soo Kim, Hyun Jin Kim, Nader Bagherzadeh

IEEE Trans. Emerg. Top. Comput., 2022

The Effects of Approximate Multiplication on Convolutional Neural Networks.

Min Soo Kim, Alberto A. Del Barrio, Hyun Jin Kim, Nader Bagherzadeh

IEEE Trans. Emerg. Top. Comput., 2022

2021

PLAM: a Posit Logarithm-Approximate Multiplier for Power Efficient Posit-based DNNs.

Raul Murillo, Alberto A. Del Barrio, Guillermo Botella, Min Soo Kim, Hyunjin Kim, Nader Bagherzadeh

CoRR, 2021

2020

Cost-Efficient Approximate Log Multipliers for Convolutional Neural Networks.

Min Soo Kim

PhD thesis, 2020

2019

Efficient Mitchell's Approximate Log Multipliers for Convolutional Neural Networks.

Min Soo Kim, Alberto A. Del Barrio, Leonardo Tavares Oliveira, Román Hermida, Nader Bagherzadeh

IEEE Trans. Computers, 2019

Design of Power-Efficient FPGA Convolutional Cores with Approximate Log Multiplier.

Leonardo Tavares Oliveira, Min Soo Kim, Alberto A. Del Barrio García, Nader Bagherzadeh, Ricardo Menotti

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

A Cost-Efficient Iterative Truncated Logarithmic Multiplication for Convolutional Neural Networks.

Hyun Jin Kim, Min Soo Kim, Alberto A. Del Barrio, Nader Bagherzadeh

Proceedings of the 26th IEEE Symposium on Computer Arithmetic, 2019

2018

Low-power implementation of Mitchell's approximate logarithmic multiplication for convolutional neural networks.

Min Soo Kim, Alberto A. Del Barrio, Román Hermida, Nader Bagherzadeh

Proceedings of the 23rd Asia and South Pacific Design Automation Conference, 2018