Improving performance of SCMA MPA decoders using estimation of conditional probabilities. - Alireza Ghaffari; Mathieu Léonardon; Yvon Savaria; Christophe Jégo; Camille Leroux (NEWCAS, 2017)

Toward High-Performance Implementation of 5G SCMA Algorithms. - Alireza Ghaffari; Mathieu Léonardon; Adrien Cassagne; Camille Leroux; Yvon Savaria (IEEE Access, 2019)

CNN2Gate: Toward Designing a General Framework for Implementation of Convolutional Neural Networks on FPGA. - Alireza Ghaffari; Yvon Savaria (CoRR, 2020)

Efficient Design Space Exploration of OpenCL Kernels for FPGA Targets Using Black Box Optimization. - Alireza Ghaffari; Yvon Savaria (IEEE Access, 2021)

Is Integer Arithmetic Enough for Deep Learning Training? - Alireza Ghaffari; Marzieh S. Tahaei; Mohammadreza Tayaranian; Masoud Asgharian; Vahid Partovi Nia (NeurIPS, 2022)

Rethinking Pareto Frontier for Performance Evaluation of Deep Neural Networks. - Vahid Partovi Nia; Alireza Ghaffari; Mahdi Zolnouri; Yvon Savaria (CoRR, 2022)

Integer Fine-tuning of Transformer-based Models. - Mohammadreza Tayaranian; Alireza Ghaffari; Marzieh S. Tahaei; Mehdi Rezagholizadeh; Masoud Asgharian; Vahid Partovi Nia (CoRR, 2022)

Towards Fine-tuning Pre-trained Language Models with Integer Forward and Backward Propagation. - Mohammadreza Tayaranian; Alireza Ghaffari; Marzieh S. Tahaei; Mehdi Rezagholizadeh; Masoud Asgharian; Vahid Partovi Nia (EACL (Findings), 2023)

On the Convergence of Stochastic Gradient Descent in Low-Precision Number Formats. - Matteo Cacciola; Antonio Frangioni; Masoud Asgharian; Alireza Ghaffari; Vahid Partovi Nia (ICPRAM, 2023)

Statistical Hardware Design With Multi-model Active Learning. - Alireza Ghaffari; Masoud Asgharian; Yvon Savaria (CoRR, 2023)

EuclidNets: An Alternative Operation for Efficient Inference of Deep Learning Models. - Xinlin Li; Mariana Parazeres; Adam Oberman; Alireza Ghaffari; Masoud Asgharian; Vahid Partovi Nia (SN Comput. Sci., 2023)

Mitigating Outlier Activations in Low-Precision Fine-Tuning of Language Models. - Alireza Ghaffari; Justin Yu; Mahsa Ghazvini Nejad; Masoud Asgharian; Boxing Chen; Vahid Partovi Nia (ICPRAM, 2024)

AdpQ: A Zero-shot Calibration Free Adaptive Post Training Quantization Method for LLMs. - Alireza Ghaffari; Sharareh Younesian; Vahid Partovi Nia; Boxing Chen; Masoud Asgharian (CoRR, 2024)

OAC: Output-adaptive Calibration for Accurate Post-training Quantization. - Ali Edalati; Alireza Ghaffari; Masoud Asgharian; Lu Hou; Boxing Chen; Vahid Partovi Nia (CoRR, 2024)

Statistical Hardware Design With Multimodel Active Learning. - Alireza Ghaffari; Masoud Asgharian; Yvon Savaria (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

DR-PIFO: A Dynamic Ranking Packet Scheduler Using a Push-In-First-Out Queue. - Mostafa Elbediwy; Bill Pontikakis; Alireza Ghaffari; Jean-Pierre David; Yvon Savaria (IEEE Trans. Netw. Serv. Manag., 2024)

OAC: Output-adaptive Calibration for Accurate Post-training Quantization. - Ali Edalati; Alireza Ghaffari; Mahsa Ghazvini Nejad; Lu Hou; Boxing Chen; Masoud Asgharian; Vahid Partovi Nia (AAAI, 2025)

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach. - Alireza Ghaffari; Sharareh Younesian; Boxing Chen; Vahid Partovi Nia; Masoud Asgharian (ICPRAM, 2025)