Generative Memory for Lifelong Learning
暂无分享,去创建一个
Xin Su | Shangqi Guo | Feng Chen | Tian Tan | Tian Tan | Shangqi Guo | Feng Chen | Xin Su
[1] Paul R. Milgrom,et al. Envelope Theorems for Arbitrary Choice Sets , 2002 .
[2] Christoph H. Lampert,et al. iCaRL: Incremental Classifier and Representation Learning , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Léon Bottou,et al. Wasserstein GAN , 2017, ArXiv.
[4] Qiang Yang,et al. Lifelong Machine Learning Systems: Beyond Learning Algorithms , 2013, AAAI Spring Symposium: Lifelong Machine Learning.
[5] Gina R Poe,et al. Sleep Is for Forgetting , 2017, The Journal of Neuroscience.
[6] Ronald Kemker,et al. FearNet: Brain-Inspired Model for Incremental Learning , 2017, ICLR.
[7] Byoung-Tak Zhang,et al. Overcoming Catastrophic Forgetting by Incremental Moment Matching , 2017, NIPS.
[8] James L. McClelland,et al. Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. , 1995, Psychological review.
[9] Andrew Y. Ng,et al. Reading Digits in Natural Images with Unsupervised Feature Learning , 2011 .
[10] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[11] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[12] Yee Whye Teh,et al. Progress & Compress: A scalable framework for continual learning , 2018, ICML.
[13] Jonathan D. Power,et al. Neural plasticity across the lifespan , 2017, Wiley interdisciplinary reviews. Developmental biology.
[14] Chrisantha Fernando,et al. PathNet: Evolution Channels Gradient Descent in Super Neural Networks , 2017, ArXiv.
[15] Eric Eaton,et al. ELLA: An Efficient Lifelong Learning Algorithm , 2013, ICML.
[16] W. Gan,et al. Branch-specific dendritic Ca2+ spikes cause persistent synaptic plasticity , 2015, Nature.
[17] Shane Legg,et al. Universal Intelligence: A Definition of Machine Intelligence , 2007, Minds and Machines.
[18] Anthony V. Robins,et al. Catastrophic Forgetting, Rehearsal and Pseudorehearsal , 1995, Connect. Sci..
[19] D. R. Euston,et al. The Role of Medial Prefrontal Cortex in Memory and Decision Making , 2012, Neuron.
[20] Ronald Kemker,et al. Measuring Catastrophic Forgetting in Neural Networks , 2017, AAAI.
[21] Surya Ganguli,et al. Continual Learning Through Synaptic Intelligence , 2017, ICML.
[22] Jiwon Kim,et al. Continual Learning with Deep Generative Replay , 2017, NIPS.
[23] Geoffrey E. Hinton. Using fast weights to deblur old memories , 1987 .
[24] Yoshua Bengio,et al. An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks , 2013, ICLR.
[25] Razvan Pascanu,et al. Overcoming catastrophic forgetting in neural networks , 2016, Proceedings of the National Academy of Sciences.
[26] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[27] Sebastian Thrun,et al. Lifelong robot learning , 1993, Robotics Auton. Syst..
[28] Michael McCloskey,et al. Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem , 1989 .
[29] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[30] D. Lewkowicz,et al. Multisensory Processes: A Balancing Act across the Lifespan , 2016, Trends in Neurosciences.
[31] Anthony V. Robins,et al. Catastrophic forgetting in neural networks: the role of rehearsal mechanisms , 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.
[32] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[33] Simon Osindero,et al. Conditional Generative Adversarial Nets , 2014, ArXiv.
[34] Derek Hoiem,et al. Learning without Forgetting , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[35] Tom Eccles,et al. Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies , 2018, NeurIPS.
[36] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[37] James L. McClelland,et al. What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated , 2016, Trends in Cognitive Sciences.
[38] C. Villani. Optimal Transport: Old and New , 2008 .
[39] Robert M. French,et al. Pseudo-recurrent Connectionist Networks: An Approach to the 'Sensitivity-Stability' Dilemma , 1997, Connect. Sci..
[40] Ruslan Salakhutdinov,et al. Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning , 2015, ICLR.
[41] Jürgen Schmidhuber,et al. Compete to Compute , 2013, NIPS.
[42] R. French. Catastrophic forgetting in connectionist networks , 1999, Trends in Cognitive Sciences.
[43] Razvan Pascanu,et al. Progressive Neural Networks , 2016, ArXiv.
[44] Richard S. Sutton,et al. Online Learning with Random Representations , 1993, ICML.
[45] Manuel Schabus,et al. Sleep transforms the cerebral trace of declarative memories , 2007, Proceedings of the National Academy of Sciences.
[46] D. Hassabis,et al. Neuroscience-Inspired Artificial Intelligence , 2017, Neuron.
[47] Alexander Gepperth,et al. A Bio-Inspired Incremental Learning Architecture for Applied Perceptual Problems , 2016, Cognitive Computation.
[48] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[49] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .