In the last few years we have witnessed a renewed and steadily growing interest in the ability to learn continuously from high-dimensional data. In this page, we will try to keep track of recent Continuous/Lifelong Learning developments in a pure research context.
In this section we keep track of the people working on the subject:
- Raia Hadsell, Razvan Pascanu - DeepMind
- Eric Eaton - University of Pennsylvania
- Bing Liu - University of Illinois at Chicago
- Vincenzo Lomonaco, Davide Maltoni - University of Bologna
In this section we keep track of all the paper published on the subject:
- Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim. “Continual Learning with Deep Generative Replay”. Advances in Neural Information Processing Systems, 2017.
- Xu He and Herbert Jaeger. “Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation”. International Conference on Learning Representations, 2018.
- Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang. “Lifelong Learning with Dynamically Expandable Networks”. International Conference on Learning Representations, 2018.
- Cuong V. Nguyen, Yingzhen Li, Thang D. Bui, and Richard E. Turner. “Variational Continual Learning”. International Conference on Learning Representations, 2018.
- Vincenzo Lomonaco and Davide Maltoni. “CORe50: a new Dataset and Benchmark for Continuous Object Recognition”. Proceedings of the 1st Annual Conference on Robot Learning, PMLR 78:17-26, 2017.
- James Kirkpatrick & All. “Overcoming catastrophic forgetting in neural networks”. Proceedings of the National Academy of Sciences, 2017, 201611835.
- Li Zhizhong and Derek Hoiem. “Learning without forgetting”. European Conference on Computer Vision. Springer International Publishing, 2016.
- Lopez-Paz David and Marc’Aurelio Ranzato. “Gradient Episodic Memory for Continual Learning”. Advances in Neural Information Processing Systems, 2017.
- Rebuffi Sylvestre-Alvise, Alexander Kolesnikov and Christoph H. Lampert. “iCaRL: Incremental classifier and representation learning.” arXiv preprint arXiv:1611.07725, 2016.
- Zenke, Friedemann, Ben Poole, and Surya Ganguli. “Continual learning through synaptic intelligence”. International Conference on Machine Learning, 2017.
- Rusu Andrei et al. “Progressive neural networks.” arXiv preprint arXiv:1606.04671, 2016.
In this section we keep track of all the current and past projects on Lifelong/Continuous Learning.: