14 citations · 16 across the 8 of their papers we have counts for
8 papers
Cat: Post-Training Quantization Error Reduction via Cluster-based Affine Transformation
Ali Zoljodi, Radu Timofte, Masoud Daneshtalab
Post-Training Quantization (PTQ) reduces the memory footprint and computational overhead of deep neural networks by converting full-precision (FP) values into quantized and compres…
TrajectoryNAS: A Neural Architecture Search for Trajectory Prediction
Ali Asghar Sharifi, Ali Zoljodi, Masoud Daneshtalab
Autonomous driving systems are a rapidly evolving technology that enables driverless car production. Trajectory prediction is a critical component of autonomous driving systems, en…
Contrastive Learning for Lane Detection via cross-similarity
Ali Zoljodi, Sadegh Abadijou, Mina Alibeigi +1
Detecting lane markings in road scenes poses a challenge due to their intricate nature, which is susceptible to unfavorable conditions. While lane markings have strong shape priors…
A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networks
Mohammad Hasan Ahmadilivani, Mahdi Taheri, Jaan Raik +2
Artificial Intelligence (AI) and, in particular, Machine Learning (ML) have emerged to be utilized in various applications due to their capability to learn how to solve complex pro…
Auto-SpMV: Automated Optimizing SpMV Kernels on GPU
Mina Ashoury, Mohammad Loni, Farshad Khunjush +1
Sparse matrix-vector multiplication (SpMV) is an essential linear algebra operation that dominates the computing cost in many scientific applications. Due to providing massive para…
Accurate Detection of Paroxysmal Atrial Fibrillation with Certified-GAN and Neural Architecture Search
Mehdi Asadi, Fatemeh Poursalim, Mohammad Loni +3
This paper presents a novel machine learning framework for detecting Paroxysmal Atrial Fibrillation (PxAF), a pathological characteristic of Electrocardiogram (ECG) that can lead t…
GTFLAT: Game Theory Based Add-On For Empowering Federated Learning Aggregation Techniques
Hamidreza Mahini, Hamid Mousavi, Masoud Daneshtalab
GTFLAT, as a game theory-based add-on, addresses an important research question: How can a federated learning algorithm achieve better performance and training efficiency by settin…
DASS: Differentiable Architecture Search for Sparse neural networks
Hamid Mousavi, Mohammad Loni, Mina Alibeigi +1
The deployment of Deep Neural Networks (DNNs) on edge devices is hindered by the substantial gap between performance requirements and available processing power. While recent resea…