29 citations · 39 across the 8 of their papers we have counts for
8 papers
Spuriosity Rankings for Free: A Simple Framework for Last Layer Retraining Based on Object Detection
Mohammad Azizmalayeri, Reza Abbasi, Amir Hosein Haji Mohammad rezaie +4
Deep neural networks have exhibited remarkable performance in various domains. However, the reliance of these models on spurious features has raised concerns about their reliabilit…
Blacksmith: Fast Adversarial Training of Vision Transformers via a Mixture of Single-step and Multi-step Methods
Mahdi Salmani, Alireza Dehghanpour Farashah, Mohammad Azizmalayeri +4
Despite the remarkable success achieved by deep learning algorithms in various domains, such as computer vision, they remain vulnerable to adversarial perturbations. Adversarial Tr…
Seeking Next Layer Neurons' Attention for Error-Backpropagation-Like Training in a Multi-Agent Network Framework
Arshia Soltani Moakhar, Mohammad Azizmalayeri, Hossein Mirzaei +2
Despite considerable theoretical progress in the training of neural networks viewed as a multi-agent system of neurons, particularly concerning biological plausibility and decentra…
A Data-Centric Approach for Improving Adversarial Training Through the Lens of Out-of-Distribution Detection
Mohammad Azizmalayeri, Arman Zarei, Alireza Isavand +2
Current machine learning models achieve super-human performance in many real-world applications. Still, they are susceptible against imperceptible adversarial perturbations. The mo…
Your Out-of-Distribution Detection Method is Not Robust!
Mohammad Azizmalayeri, Arshia Soltani Moakhar, Arman Zarei +3
Out-of-distribution (OOD) detection has recently gained substantial attention due to the importance of identifying out-of-domain samples in reliability and safety. Although OOD det…
A Bayesian Approach to the Data Description Problem
Alireza Ghasemi, Hamid R. Rabiee, Mohammad T. Manzuri +1
In this paper, we address the problem of data description using a Bayesian framework. The goal of data description is to draw a boundary around objects of a certain class of intere…
Active Learning from Positive and Unlabeled Data
Alireza Ghasemi, Hamid R. Rabiee, Mohsen Fadaee +2
During recent years, active learning has evolved into a popular paradigm for utilizing user's feedback to improve accuracy of learning algorithms. Active learning works by selectin…
Facial Expression Representation and Recognition Using 2DHLDA, Gabor Wavelets, and Ensemble Learning
Mahmoud Khademi, Mohammad H. Kiapour, Mehran Safayani +2
In this paper, a novel method for representation and recognition of the facial expressions in two-dimensional image sequences is presented. We apply a variation of two-dimensional…