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Mustafa Burak Gurbuz

2 accepted papers

2025

PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity

ICML 2025poster

As deep learning continues to be driven by ever-larger datasets, understanding which examples are most important for generalization has become a critical question. While progress in data selection continues, emerging applications require studying this problem in dynamic contexts. To bridge this gap,…

2024

NICE: Neurogenesis Inspired Contextual Encoding for Replay-free Class Incremental Learning

CVPR 2024poster

Deep neural networks (DNNs) struggle to learn in dynamic settings because they mainly rely on static datasets. Continual learning (CL) aims to overcome this limitation by enabling DNNs to incrementally accumulate knowledge. A widely adopted scenario in CL is class-incremental learning (CIL) where DN…