18 citations · 32 across the 13 of their papers we have counts for
15 papers
A Hierarchical Importance-Guided Multi-objective Evolutionary Framework for Deep Neural Network Pruning
Zak Khan, Azam Asilian Bidgoli
The optimization of over-parameterized deep neural networks represents a large-scale, high-dimensional, and strongly non-convex decision problem that challenges existing optimizati…
Med-SegLens: Latent-Level Model Diffing for Interpretable Medical Image Segmentation
Salma J. Ahmed, Emad A. Mohammed, Azam Asilian Bidgoli
Modern segmentation models achieve strong predictive performance but remain largely opaque, limiting our ability to diagnose failures, understand dataset shift, or intervene in a p…
EvoPS: Evolutionary Patch Selection for Whole Slide Image Analysis in Computational Pathology
Saya Hashemian, Azam Asilian Bidgoli
In computational pathology, the gigapixel scale of Whole-Slide Images (WSIs) necessitates their division into thousands of smaller patches. Analyzing these high-dimensional patch e…
J-RAS: Mutual Adaptation for Medical Image Segmentation via Contrastive Retrieval-Augmented Joint Optimization
Salma J. Ahmed, Emad A. Mohammed, Azam Asilian Bidgoli
Manual medical image segmentation by clinicians, though accurate, is time-consuming and variable across experts, while AI-based models automate this process but often falter under…
Evolutionary Feature-wise Thresholding for Binary Representation of NLP Embeddings
Soumen Sinha, Shahryar Rahnamayan, Azam Asilian Bidgoli
Efficient text embedding is crucial for large-scale natural language processing (NLP) applications, where storage and computational efficiency are key concerns. In this paper, we e…
A Novel Pareto-optimal Ranking Method for Comparing Multi-objective Optimization Algorithms
Amin Ibrahim, Azam Asilian Bidgoli, Shahryar Rahnamayan +1
As the interest in multi- and many-objective optimization algorithms grows, the performance comparison of these algorithms becomes increasingly important. A large number of perform…