activity
20192024
most citedLearning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System

37 citations · 61 across the 27 of their papers we have counts for

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Showing cs.LGShow all

14 papers · 1 filter

cs.LG2024

IMEX-Reg: Implicit-Explicit Regularization in the Function Space for Continual Learning

Prashant Bhat, Bharath Renjith, Elahe Arani +1

Continual learning (CL) remains one of the long-standing challenges for deep neural networks due to catastrophic forgetting of previously acquired knowledge. Although rehearsal-bas…

cs.LG2024

The Effectiveness of Random Forgetting for Robust Generalization

Vijaya Raghavan T Ramkumar, Bahram Zonooz, Elahe Arani

Deep neural networks are susceptible to adversarial attacks, which can compromise their performance and accuracy. Adversarial Training (AT) has emerged as a popular approach for pr…

cs.LG20241 cited

Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training

Shruthi Gowda, Bahram Zonooz, Elahe Arani

Adversarial training improves the robustness of neural networks against adversarial attacks, albeit at the expense of the trade-off between standard and robust generalization. To u…

cs.LG2023

Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal

Naresh Kumar Gurulingan, Bahram Zonooz, Elahe Arani

Multi-task learning has the potential to improve generalization by maximizing positive transfer between tasks while reducing task interference. Fully achieving this potential is hi…

cs.LG20232 cited

Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks

Vijaya Raghavan T. Ramkumar, Elahe Arani, Bahram Zonooz

Deep neural networks (DNNs) are often trained on the premise that the complete training data set is provided ahead of time. However, in real-world scenarios, data often arrive in c…

cs.LG20235 cited

Task-Aware Information Routing from Common Representation Space in Lifelong Learning

Prashant Bhat, Bahram Zonooz, Elahe Arani

Intelligent systems deployed in the real world suffer from catastrophic forgetting when exposed to a sequence of tasks. Humans, on the other hand, acquire, consolidate, and transfe…