26 citations · 53 across the 7 of their papers we have counts for
5 papers · 1 filter
PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity
Mustafa Burak Gurbuz, Xingyu Zheng, Constantine Dovrolis
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 i…
Class-Incremental Continual Learning for General Purpose Healthcare Models
Amritpal Singh, Mustafa Burak Gurbuz, Shiva Souhith Gantha +1
Healthcare clinics regularly encounter dynamic data that changes due to variations in patient populations, treatment policies, medical devices, and emerging disease patterns. Deep…
SHARP: Sparsity and Hidden Activation RePlay for Neuro-Inspired Continual Learning
Mustafa Burak Gurbuz, Jean Michael Moorman, Constantine Dovrolis
Deep neural networks (DNNs) struggle to learn in dynamic environments since they rely on fixed datasets or stationary environments. Continual learning (CL) aims to address this lim…
System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games
Indranil Sur, Zachary Daniels, Abrar Rahman +16
As Artificial and Robotic Systems are increasingly deployed and relied upon for real-world applications, it is important that they exhibit the ability to continually learn and adap…
NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks
Mustafa Burak Gurbuz, Constantine Dovrolis
The goal of continual learning (CL) is to learn different tasks over time. The main desiderata associated with CL are to maintain performance on older tasks, leverage the latter to…