activity
20192022
most citedThe Effects of Approximate Multiplication on Convolutional Neural Networks

73 citations · 172 across the 5 of their papers we have counts for

collaborators

6 papers

eess.SP2022

A Two-Stage Efficient 3-D CNN Framework for EEG Based Emotion Recognition

Ye Qiao, Mohammed Alnemari, Nader Bagherzadeh

This paper proposes a novel two-stage framework for emotion recognition using EEG data that outperforms state-of-the-art models while keeping the model size small and computational…

cs.LG2021★ 57 cited

PLAM: a Posit Logarithm-Approximate Multiplier

Raul Murillo, Alberto A. Del Barrio, Guillermo Botella +3

The Posit Number System was introduced in 2017 as a replacement for floating-point numbers. Since then, the community has explored its application in Neural Network related tasks a…

cs.LG2020★ 73 cited

The Effects of Approximate Multiplication on Convolutional Neural Networks

Min Soo Kim, Alberto A. Del Barrio, HyunJin Kim +1

This paper analyzes the effects of approximate multiplication when performing inferences on deep convolutional neural networks (CNNs). The approximate multiplication can reduce the…

cs.LG2020

Reliable and Energy Efficient MLC STT-RAM Buffer for CNN Accelerators

Masoomeh Jasemi, Shaahin Hessabi, Nader Bagherzadeh

We propose a lightweight scheme where the formation of a data block is changed in such a way that it can tolerate soft errors significantly better than the baseline. The key insigh…

physics.app-ph2019★ 36 cited

Immunity of nanoscale magnetic tunnel junctions to ionizing radiation

Eric Arturo Montoya, Jen-Ru Chen, Randy Ngelale +9

Spin transfer torque magnetic random access memory (STT-MRAM) is a promising candidate for next generation memory as it is non-volatile, fast, and has unlimited endurance. Another…

cs.CV2019★ 6 cited

Partition Pruning: Parallelization-Aware Pruning for Deep Neural Networks

Sina Shahhosseini, Ahmad Albaqsami, Masoomeh Jasemi +1

Parameters of recent neural networks require a huge amount of memory. These parameters are used by neural networks to perform machine learning tasks when processing inputs. To spee…