3 citations · 5 across the 8 of their papers we have counts for
8 papers
Shapley Neuron Values for Continual Learning: Which Neurons Matter Most?
Mohammad Ali Vahedifar, Abhisek Ray, Qi Zhang
Continual learning enables neural networks to learn tasks sequentially without forgetting previously acquired knowledge. However, neural networks suffer from catastrophic forgettin…
Continuous Orthogonal Mode Decomposition: Haptic Signal Prediction in Tactile Internet
Mohammad Ali Vahedifar, Mojtaba Nazari, Qi Zhang
The Tactile Internet demands sub-millisecond latency and ultra-high reliability, as even slight latency or packet loss can destabilize haptic control. To address this, we propose t…
Discrete Mode Decomposition Meets Shapley Value: Robust Signal Prediction in Tactile Internet
Mohammad Ali Vahedifar, Qi Zhang
Tactile Internet (TI) requires ultra-low latency and high reliability to ensure stability and transparency in touch-enabled teleoperation. However, variable delays and packet loss…
Shapley Features for Robust Signal Prediction in Tactile Internet
Mohammad Ali Vahedifar, Qi Zhang
The Tactile Internet (TI) requires ultra-low latency and reliable haptic signal transmission, yet packet loss and delay remain unresolved challenges. We present a novel prediction…
Signal Prediction for Loss Mitigation in Tactile Internet: A Leader-Follower Game-Theoretic Approach
Mohammad Ali Vahedifar, Qi Zhang
Tactile Internet (TI) requires achieving ultra-low latency and highly reliable packet delivery for haptic signals. In the presence of packet loss and delay, the signal prediction m…
No Forgetting Learning: Buffer-free Continual Learning Classification
Mohammad Ali Vahedifar, Qi Zhang
Most Continual Learning (CL) methods maintain performance on earlier tasks by storing exemplars in a replay buffer, introducing memory overhead that scales with the number of tasks…
Shapley-Based Data Valuation with Mutual Information: A Key to Modified K-Nearest Neighbors
Mohammad Ali Vahedifar, Azim Akhtarshenas, Mohammad Mohammadi Rafatpanah +1
The K-Nearest Neighbors (KNN) algorithm is widely used for classification and regression; however, it suffers from limitations, including the equal treatment of all samples. We pro…
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and Applications
Azim Akhtarshenas, Mohammad Ali Vahedifar, Navid Ayoobi +4
Robust machine learning (ML) models can be developed by leveraging large volumes of data and distributing the computational tasks across numerous devices or servers. Federated lear…