4 papers
Domain-Aware Pruning: Sparsity and Domain Generalization via Regularized Probabilistic Masking
Parham Sazdar, Mostafa Tavassolipour, Reshad Hosseini
Domain generalization (DG) and neural network pruning are conventionally treated as distinct objectives, targeting out-of-distribution (OOD) robustness and model efficiency, respec…
Improving Adversarial Robustness of Zero-Shot CLIP with Confidence-Aware Weighting
Nikoo Naghavian, Mostafa Tavassolipour
Vision-language models such as CLIP demonstrate impressive zero-shot generalization but remain highly vulnerable to adversarial attacks. Prior adversarial methods treat all samples…
Robustifying Diffusion-Denoised Smoothing Against Covariate Shift
Ali Hedayatnia, Mostafa Tavassolipour, Babak Nadjar Araabi +1
Randomized smoothing is a well-established method for achieving certified robustness against l2-adversarial perturbations. By incorporating a denoiser before the base classifier, p…
FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection
Sina Najafi, Mostafa Tavassolipour, Mohammad Hasan Narimani
Federated learning (FL) enables collaborative model training without centralizing data, but exchanging high-dimensional updates can expose sensitive information and incur substanti…