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Continual Learning

1,929 papers

Papers per year

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Papers

Continual Unsupervised Representation Learning NIPS 2019
MetaInit: Initializing learning by learning to initialize NIPS 2019
Practical Deep Learning with Bayesian Principles NIPS 2019
Inherent Weight Normalization in Stochastic Neural Networks NIPS 2019
Gradient based sample selection for online continual learning NIPS 2019
Meta-Learning Representations for Continual Learning NIPS 2019
Episodic Memory in Lifelong Language Learning NIPS 2019
Experience Replay for Continual Learning NIPS 2019
Locally Weighted Regression Pseudo-Rehearsal for Adaptive Model Predictive Control CORL 2019
Scalable Recollections for Continual Lifelong Learning AAAI 2019
Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting AAAI 2019
Multi-Task Deep Reinforcement Learning with PopArt AAAI 2019
Meta-Descent for Online, Continual Prediction AAAI 2019
Evolutionary Manytasking Optimization Based on Symbiosis in Biocoenosis AAAI 2019
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning AAAI 2019
Dynamically Composing Domain-Data Selection with Clean-Data Selection by “Co-Curricular Learning” for Neural Machine Translation ACL 2019
Continual and Multi-Task Architecture Search ACL 2019
Psycholinguistics Meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering ACL 2019
Incremental Learning from Scratch for Task-Oriented Dialogue Systems ACL 2019
Towards Incremental Learning of Word Embeddings Using Context Informativeness ACL 2019
Meta-Learning Improves Lifelong Relation Extraction ACL 2019
Forward and Backward Knowledge Transfer for Sentiment Classification ACML 2019
Lifelong Optimization with Low Regret AISTATS 2019
Real-Time Self-Adaptive Deep Stereo CVPR 2019
Large Scale Incremental Learning CVPR 2019