8 citations · 18 across the 4 of their papers we have counts for
6 papers
Sharpness-Aware Parameter Selection for Machine Unlearning
Saber Malekmohammadi, Hong kyu Lee, Li Xiong
It often happens that some sensitive personal information, such as credit card numbers or passwords, are mistakenly incorporated in the training of machine learning models and need…
LoRA Provides Differential Privacy by Design via Random Sketching
Saber Malekmohammadi, Golnoosh Farnadi
Low-rank adaptation of language models has been proposed to reduce the computational and memory overhead of fine-tuning pre-trained language models. LoRA incorporates trainable low…
PePScenes: A Novel Dataset and Baseline for Pedestrian Action Prediction in 3D
Amir Rasouli, Tiffany Yau, Peter Lakner +3
Predicting the behavior of road users, particularly pedestrians, is vital for safe motion planning in the context of autonomous driving systems. Traditionally, pedestrian behavior…
Graph-SIM: A Graph-based Spatiotemporal Interaction Modelling for Pedestrian Action Prediction
Tiffany Yau, Saber Malekmohammadi, Amir Rasouli +3
One of the most crucial yet challenging tasks for autonomous vehicles in urban environments is predicting the future behaviour of nearby pedestrians, especially at points of crossi…
Non-Parametric Graph Learning for Bayesian Graph Neural Networks
Soumyasundar Pal, Saber Malekmohammadi, Florence Regol +3
Graphs are ubiquitous in modelling relational structures. Recent endeavours in machine learning for graph-structured data have led to many architectures and learning algorithms. Ho…
Sparsity Promoting Reconstruction of Delta Modulated Voice Samples by Sequential Adaptive Thresholds
Mahdi Boloursaz Mashhadi, Saber Malekmohammadi, Farokh Marvasti
In this paper, we propose the family of Iterative Methods with Adaptive Thresholding (IMAT) for sparsity promoting reconstruction of Delta Modulated (DM) voice signals. We suggest…