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Continual Learning

557 directly classified papers

Papers per year

Papers

Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem CVPR 2020
Few-Shot Class-Incremental Learning CVPR 2020
iTAML: An Incremental Task-Agnostic Meta-learning Approach CVPR 2020
Sequential Mastery of Multiple Visual Tasks: Networks Naturally Learn to Learn and Forget to Forget CVPR 2020
Continual Learning With Extended Kronecker-Factored Approximate Curvature CVPR 2020
ADINet: Attribute Driven Incremental Network for Retinal Image Classification CVPR 2020
Regularize, Expand and Compress: NonExpansive Continual Learning WACV 2020
Residual Continual Learning AAAI 2020
Deep Streaming Label Learning ICML 2020
Understanding the Role of Training Regimes in Continual Learning NIPS 2020
Disentangle-based Continual Graph Representation Learning EMNLP 2020
Using the Past Knowledge to Improve Sentiment Classification EMNLP 2020
Continual Deep Learning by Functional Regularisation of Memorable Past NIPS 2020
Class-incremental Learning via Deep Model Consolidation WACV 2020
Findings of the First Shared Task on Lifelong Learning Machine Translation EMNLP 2020
Continuous Meta-Learning without Tasks NIPS 2020
Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization NIPS 2020
Supermasks in Superposition NIPS 2020
Coresets via Bilevel Optimization for Continual Learning and Streaming NIPS 2020
Continual Learning in Low-rank Orthogonal Subspaces NIPS 2020
Continual Relation Learning via Episodic Memory Activation and Reconsolidation ACL 2020
Biologically Inspired Sleep Algorithm for Reducing Catastrophic Forgetting in Neural Networks AAAI 2020
ERNIE 2.0: A Continual Pre-Training Framework for Language Understanding AAAI 2020
Bi-Objective Continual Learning: Learning ‘New’ While Consolidating ‘Known’ AAAI 2020
Generative Continual Concept Learning AAAI 2020