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**[26]** Iandola, Forrest N., et al. "**SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 1MB model size**." arXiv preprint arXiv:1602.07360 (2016). [[pdf]](http://arxiv.org/pdf/1602.07360)**(Also a new direction to optimize NN,DeePhi Tech Startup)**:star::star::star::star:
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**[27]** Glorat Xavier, Bengio Yoshua, et al. "**Understanding the difficulty of training deep forward neural networks**." Proceedings of the thirteenth International Conference on Artificial Intelligence and Statistics, PMLR 9:249-256,2010. [[pdf]](http://proceedings.mlr.press/v9/glorot10a/glorot10a.pdf):star::star::star::star:
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## 2.3 Unsupervised Learning / Deep Generative Model
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**[27]** Le, Quoc V. "**Building high-level features using large scale unsupervised learning**." 2013 IEEE international conference on acoustics, speech and signal processing. IEEE, 2013. [[pdf]](http://arxiv.org/pdf/1112.6209.pdf&embed)**(Milestone, Andrew Ng, Google Brain Project, Cat)**:star::star::star::star:
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**[28]** Le, Quoc V. "**Building high-level features using large scale unsupervised learning**." 2013 IEEE international conference on acoustics, speech and signal processing. IEEE, 2013. [[pdf]](http://arxiv.org/pdf/1112.6209.pdf&embed)**(Milestone, Andrew Ng, Google Brain Project, Cat)**:star::star::star::star:
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**[28]** Kingma, Diederik P., and Max Welling. "**Auto-encoding variational bayes**." arXiv preprint arXiv:1312.6114 (2013). [[pdf]](http://arxiv.org/pdf/1312.6114)**(VAE)**:star::star::star::star:
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**[29]** Kingma, Diederik P., and Max Welling. "**Auto-encoding variational bayes**." arXiv preprint arXiv:1312.6114 (2013). [[pdf]](http://arxiv.org/pdf/1312.6114)**(VAE)**:star::star::star::star:
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**[29]** Goodfellow, Ian, et al. "**Generative adversarial nets**." Advances in Neural Information Processing Systems. 2014. [[pdf]](http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf)**(GAN,super cool idea)**:star::star::star::star::star:
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**[30]** Goodfellow, Ian, et al. "**Generative adversarial nets**." Advances in Neural Information Processing Systems. 2014. [[pdf]](http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf)**(GAN,super cool idea)**:star::star::star::star::star:
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**[30]** Radford, Alec, Luke Metz, and Soumith Chintala. "**Unsupervised representation learning with deep convolutional generative adversarial networks**." arXiv preprint arXiv:1511.06434 (2015). [[pdf]](http://arxiv.org/pdf/1511.06434)**(DCGAN)**:star::star::star::star:
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**[31]** Radford, Alec, Luke Metz, and Soumith Chintala. "**Unsupervised representation learning with deep convolutional generative adversarial networks**." arXiv preprint arXiv:1511.06434 (2015). [[pdf]](http://arxiv.org/pdf/1511.06434)**(DCGAN)**:star::star::star::star:
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**[31]** Gregor, Karol, et al. "**DRAW: A recurrent neural network for image generation**." arXiv preprint arXiv:1502.04623 (2015). [[pdf]](http://jmlr.org/proceedings/papers/v37/gregor15.pdf)**(VAE with attention, outstanding work)**:star::star::star::star::star:
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**[32]** Gregor, Karol, et al. "**DRAW: A recurrent neural network for image generation**." arXiv preprint arXiv:1502.04623 (2015). [[pdf]](http://jmlr.org/proceedings/papers/v37/gregor15.pdf)**(VAE with attention, outstanding work)**:star::star::star::star::star:
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**[32]** Oord, Aaron van den, Nal Kalchbrenner, and Koray Kavukcuoglu. "**Pixel recurrent neural networks**." arXiv preprint arXiv:1601.06759 (2016). [[pdf]](http://arxiv.org/pdf/1601.06759)**(PixelRNN)**:star::star::star::star:
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**[33]** Oord, Aaron van den, Nal Kalchbrenner, and Koray Kavukcuoglu. "**Pixel recurrent neural networks**." arXiv preprint arXiv:1601.06759 (2016). [[pdf]](http://arxiv.org/pdf/1601.06759)**(PixelRNN)**:star::star::star::star:
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**[33]** Oord, Aaron van den, et al. "Conditional image generation with PixelCNN decoders." arXiv preprint arXiv:1606.05328 (2016). [[pdf]](https://arxiv.org/pdf/1606.05328)**(PixelCNN)**:star::star::star::star:
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**[34]** Oord, Aaron van den, et al. "Conditional image generation with PixelCNN decoders." arXiv preprint arXiv:1606.05328 (2016). [[pdf]](https://arxiv.org/pdf/1606.05328)**(PixelCNN)**:star::star::star::star:
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## 2.4 RNN / Sequence-to-Sequence Model
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**[34]** Graves, Alex. "**Generating sequences with recurrent neural networks**." arXiv preprint arXiv:1308.0850 (2013). [[pdf]](http://arxiv.org/pdf/1308.0850)**(LSTM, very nice generating result, show the power of RNN)**:star::star::star::star:
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**[35]** Graves, Alex. "**Generating sequences with recurrent neural networks**." arXiv preprint arXiv:1308.0850 (2013). [[pdf]](http://arxiv.org/pdf/1308.0850)**(LSTM, very nice generating result, show the power of RNN)**:star::star::star::star:
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**[35]** Cho, Kyunghyun, et al. "**Learning phrase representations using RNN encoder-decoder for statistical machine translation**." arXiv preprint arXiv:1406.1078 (2014). [[pdf]](http://arxiv.org/pdf/1406.1078)**(First Seq-to-Seq Paper)**:star::star::star::star:
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**[36]** Cho, Kyunghyun, et al. "**Learning phrase representations using RNN encoder-decoder for statistical machine translation**." arXiv preprint arXiv:1406.1078 (2014). [[pdf]](http://arxiv.org/pdf/1406.1078)**(First Seq-to-Seq Paper)**:star::star::star::star:
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**[36]** Sutskever, Ilya, Oriol Vinyals, and Quoc V. Le. "**Sequence to sequence learning with neural networks**." Advances in neural information processing systems. 2014. [[pdf]](https://arxiv.org/pdf/1409.3215.pdf)**(Outstanding Work)**:star::star::star::star::star:
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**[37]** Sutskever, Ilya, Oriol Vinyals, and Quoc V. Le. "**Sequence to sequence learning with neural networks**." Advances in neural information processing systems. 2014. [[pdf]](https://arxiv.org/pdf/1409.3215.pdf)**(Outstanding Work)**:star::star::star::star::star:
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**[37]** Bahdanau, Dzmitry, KyungHyun Cho, and Yoshua Bengio. "**Neural Machine Translation by Jointly Learning to Align and Translate**." arXiv preprint arXiv:1409.0473 (2014). [[pdf]](https://arxiv.org/pdf/1409.0473v7.pdf):star::star::star::star:
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**[38]** Bahdanau, Dzmitry, KyungHyun Cho, and Yoshua Bengio. "**Neural Machine Translation by Jointly Learning to Align and Translate**." arXiv preprint arXiv:1409.0473 (2014). [[pdf]](https://arxiv.org/pdf/1409.0473v7.pdf):star::star::star::star:
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**[38]** Vinyals, Oriol, and Quoc Le. "**A neural conversational model**." arXiv preprint arXiv:1506.05869 (2015). [[pdf]](http://arxiv.org/pdf/1506.05869.pdf%20(http://arxiv.org/pdf/1506.05869.pdf))**(Seq-to-Seq on Chatbot)**:star::star::star:
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**[39]** Vinyals, Oriol, and Quoc Le. "**A neural conversational model**." arXiv preprint arXiv:1506.05869 (2015). [[pdf]](http://arxiv.org/pdf/1506.05869.pdf%20(http://arxiv.org/pdf/1506.05869.pdf))**(Seq-to-Seq on Chatbot)**:star::star::star:
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## 2.5 Neural Turing Machine
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**[39]** Graves, Alex, Greg Wayne, and Ivo Danihelka. "**Neural turing machines**." arXiv preprint arXiv:1410.5401 (2014). [[pdf]](http://arxiv.org/pdf/1410.5401.pdf)**(Basic Prototype of Future Computer)**:star::star::star::star::star:
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**[40]** Graves, Alex, Greg Wayne, and Ivo Danihelka. "**Neural turing machines**." arXiv preprint arXiv:1410.5401 (2014). [[pdf]](http://arxiv.org/pdf/1410.5401.pdf)**(Basic Prototype of Future Computer)**:star::star::star::star::star:
**[41]** Weston, Jason, Sumit Chopra, and Antoine Bordes. "**Memory networks**." arXiv preprint arXiv:1410.3916 (2014). [[pdf]](http://arxiv.org/pdf/1410.3916):star::star::star:
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**[42]** Weston, Jason, Sumit Chopra, and Antoine Bordes. "**Memory networks**." arXiv preprint arXiv:1410.3916 (2014). [[pdf]](http://arxiv.org/pdf/1410.3916):star::star::star:
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**[42]** Sukhbaatar, Sainbayar, Jason Weston, and Rob Fergus. "**End-to-end memory networks**." Advances in neural information processing systems. 2015. [[pdf]](http://papers.nips.cc/paper/5846-end-to-end-memory-networks.pdf):star::star::star::star:
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**[43]** Sukhbaatar, Sainbayar, Jason Weston, and Rob Fergus. "**End-to-end memory networks**." Advances in neural information processing systems. 2015. [[pdf]](http://papers.nips.cc/paper/5846-end-to-end-memory-networks.pdf):star::star::star::star:
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**[43]** Vinyals, Oriol, Meire Fortunato, and Navdeep Jaitly. "**Pointer networks**." Advances in Neural Information Processing Systems. 2015. [[pdf]](http://papers.nips.cc/paper/5866-pointer-networks.pdf):star::star::star::star:
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**[44]** Vinyals, Oriol, Meire Fortunato, and Navdeep Jaitly. "**Pointer networks**." Advances in Neural Information Processing Systems. 2015. [[pdf]](http://papers.nips.cc/paper/5866-pointer-networks.pdf):star::star::star::star:
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**[44]** Graves, Alex, et al. "**Hybrid computing using a neural network with dynamic external memory**." Nature (2016). [[pdf]](https://www.dropbox.com/s/0a40xi702grx3dq/2016-graves.pdf)**(Milestone,combine above papers' ideas)**:star::star::star::star::star:
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**[45]** Graves, Alex, et al. "**Hybrid computing using a neural network with dynamic external memory**." Nature (2016). [[pdf]](https://www.dropbox.com/s/0a40xi702grx3dq/2016-graves.pdf)**(Milestone,combine above papers' ideas)**:star::star::star::star::star:
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## 2.6 Deep Reinforcement Learning
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**[45]** Mnih, Volodymyr, et al. "**Playing atari with deep reinforcement learning**." arXiv preprint arXiv:1312.5602 (2013). [[pdf]](http://arxiv.org/pdf/1312.5602.pdf)) **(First Paper named deep reinforcement learning)**:star::star::star::star:
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**[46]** Mnih, Volodymyr, et al. "**Playing atari with deep reinforcement learning**." arXiv preprint arXiv:1312.5602 (2013). [[pdf]](http://arxiv.org/pdf/1312.5602.pdf)) **(First Paper named deep reinforcement learning)**:star::star::star::star:
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**[46]** Mnih, Volodymyr, et al. "**Human-level control through deep reinforcement learning**." Nature 518.7540 (2015): 529-533. [[pdf]](https://storage.googleapis.com/deepmind-data/assets/papers/DeepMindNature14236Paper.pdf)**(Milestone)**:star::star::star::star::star:
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**[47]** Mnih, Volodymyr, et al. "**Human-level control through deep reinforcement learning**." Nature 518.7540 (2015): 529-533. [[pdf]](https://storage.googleapis.com/deepmind-data/assets/papers/DeepMindNature14236Paper.pdf)**(Milestone)**:star::star::star::star::star:
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**[47]** Wang, Ziyu, Nando de Freitas, and Marc Lanctot. "**Dueling network architectures for deep reinforcement learning**." arXiv preprint arXiv:1511.06581 (2015). [[pdf]](http://arxiv.org/pdf/1511.06581)**(ICLR best paper,great idea)**:star::star::star::star:
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**[48]** Wang, Ziyu, Nando de Freitas, and Marc Lanctot. "**Dueling network architectures for deep reinforcement learning**." arXiv preprint arXiv:1511.06581 (2015). [[pdf]](http://arxiv.org/pdf/1511.06581)**(ICLR best paper,great idea)**:star::star::star::star:
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**[48]** Mnih, Volodymyr, et al. "**Asynchronous methods for deep reinforcement learning**." arXiv preprint arXiv:1602.01783 (2016). [[pdf]](http://arxiv.org/pdf/1602.01783)**(State-of-the-art method)**:star::star::star::star::star:
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**[49]** Mnih, Volodymyr, et al. "**Asynchronous methods for deep reinforcement learning**." arXiv preprint arXiv:1602.01783 (2016). [[pdf]](http://arxiv.org/pdf/1602.01783)**(State-of-the-art method)**:star::star::star::star::star:
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**[49]** Lillicrap, Timothy P., et al. "**Continuous control with deep reinforcement learning**." arXiv preprint arXiv:1509.02971 (2015). [[pdf]](http://arxiv.org/pdf/1509.02971)**(DDPG)**:star::star::star::star:
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**[50]** Lillicrap, Timothy P., et al. "**Continuous control with deep reinforcement learning**." arXiv preprint arXiv:1509.02971 (2015). [[pdf]](http://arxiv.org/pdf/1509.02971)**(DDPG)**:star::star::star::star:
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**[50]** Gu, Shixiang, et al. "**Continuous Deep Q-Learning with Model-based Acceleration**." arXiv preprint arXiv:1603.00748 (2016). [[pdf]](http://arxiv.org/pdf/1603.00748)**(NAF)**:star::star::star::star:
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**[51]** Gu, Shixiang, et al. "**Continuous Deep Q-Learning with Model-based Acceleration**." arXiv preprint arXiv:1603.00748 (2016). [[pdf]](http://arxiv.org/pdf/1603.00748)**(NAF)**:star::star::star::star:
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**[51]** Schulman, John, et al. "**Trust region policy optimization**." CoRR, abs/1502.05477 (2015). [[pdf]](http://www.jmlr.org/proceedings/papers/v37/schulman15.pdf)**(TRPO)**:star::star::star::star:
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**[52]** Schulman, John, et al. "**Trust region policy optimization**." CoRR, abs/1502.05477 (2015). [[pdf]](http://www.jmlr.org/proceedings/papers/v37/schulman15.pdf)**(TRPO)**:star::star::star::star:
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**[52]** Silver, David, et al. "**Mastering the game of Go with deep neural networks and tree search**." Nature 529.7587 (2016): 484-489. [[pdf]](http://willamette.edu/~levenick/cs448/goNature.pdf)**(AlphaGo)**:star::star::star::star::star:
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**[53]** Silver, David, et al. "**Mastering the game of Go with deep neural networks and tree search**." Nature 529.7587 (2016): 484-489. [[pdf]](http://willamette.edu/~levenick/cs448/goNature.pdf)**(AlphaGo)**:star::star::star::star::star:
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## 2.7 Deep Transfer Learning / Lifelong Learning / especially for RL
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**[53]** Bengio, Yoshua. "**Deep Learning of Representations for Unsupervised and Transfer Learning**." ICML Unsupervised and Transfer Learning 27 (2012): 17-36. [[pdf]](http://www.jmlr.org/proceedings/papers/v27/bengio12a/bengio12a.pdf)**(A Tutorial)**:star::star::star:
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**[54]** Bengio, Yoshua. "**Deep Learning of Representations for Unsupervised and Transfer Learning**." ICML Unsupervised and Transfer Learning 27 (2012): 17-36. [[pdf]](http://www.jmlr.org/proceedings/papers/v27/bengio12a/bengio12a.pdf)**(A Tutorial)**:star::star::star:
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**[54]** Silver, Daniel L., Qiang Yang, and Lianghao Li. "**Lifelong Machine Learning Systems: Beyond Learning Algorithms**." AAAI Spring Symposium: Lifelong Machine Learning. 2013. [[pdf]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.696.7800&rep=rep1&type=pdf)**(A brief discussion about lifelong learning)**:star::star::star:
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**[55]** Silver, Daniel L., Qiang Yang, and Lianghao Li. "**Lifelong Machine Learning Systems: Beyond Learning Algorithms**." AAAI Spring Symposium: Lifelong Machine Learning. 2013. [[pdf]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.696.7800&rep=rep1&type=pdf)**(A brief discussion about lifelong learning)**:star::star::star:
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**[55]** Hinton, Geoffrey, Oriol Vinyals, and Jeff Dean. "**Distilling the knowledge in a neural network**." arXiv preprint arXiv:1503.02531 (2015). [[pdf]](http://arxiv.org/pdf/1503.02531)**(Godfather's Work)**:star::star::star::star:
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**[56]** Hinton, Geoffrey, Oriol Vinyals, and Jeff Dean. "**Distilling the knowledge in a neural network**." arXiv preprint arXiv:1503.02531 (2015). [[pdf]](http://arxiv.org/pdf/1503.02531)**(Godfather's Work)**:star::star::star::star:
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**[56]** Rusu, Andrei A., et al. "**Policy distillation**." arXiv preprint arXiv:1511.06295 (2015). [[pdf]](http://arxiv.org/pdf/1511.06295)**(RL domain)**:star::star::star:
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**[57]** Rusu, Andrei A., et al. "**Policy distillation**." arXiv preprint arXiv:1511.06295 (2015). [[pdf]](http://arxiv.org/pdf/1511.06295)**(RL domain)**:star::star::star:
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**[57]** Parisotto, Emilio, Jimmy Lei Ba, and Ruslan Salakhutdinov. "**Actor-mimic: Deep multitask and transfer reinforcement learning**." arXiv preprint arXiv:1511.06342 (2015). [[pdf]](http://arxiv.org/pdf/1511.06342)**(RL domain)**:star::star::star:
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**[58]** Parisotto, Emilio, Jimmy Lei Ba, and Ruslan Salakhutdinov. "**Actor-mimic: Deep multitask and transfer reinforcement learning**." arXiv preprint arXiv:1511.06342 (2015). [[pdf]](http://arxiv.org/pdf/1511.06342)**(RL domain)**:star::star::star:
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**[58]** Rusu, Andrei A., et al. "**Progressive neural networks**." arXiv preprint arXiv:1606.04671 (2016). [[pdf]](https://arxiv.org/pdf/1606.04671)**(Outstanding Work, A novel idea)**:star::star::star::star::star:
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**[59]** Rusu, Andrei A., et al. "**Progressive neural networks**." arXiv preprint arXiv:1606.04671 (2016). [[pdf]](https://arxiv.org/pdf/1606.04671)**(Outstanding Work, A novel idea)**:star::star::star::star::star:
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## 2.8 One Shot Deep Learning
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**[59]** Lake, Brenden M., Ruslan Salakhutdinov, and Joshua B. Tenenbaum. "**Human-level concept learning through probabilistic program induction**." Science 350.6266 (2015): 1332-1338. [[pdf]](http://clm.utexas.edu/compjclub/wp-content/uploads/2016/02/lake2015.pdf)**(No Deep Learning,but worth reading)**:star::star::star::star::star:
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**[60]** Lake, Brenden M., Ruslan Salakhutdinov, and Joshua B. Tenenbaum. "**Human-level concept learning through probabilistic program induction**." Science 350.6266 (2015): 1332-1338. [[pdf]](http://clm.utexas.edu/compjclub/wp-content/uploads/2016/02/lake2015.pdf)**(No Deep Learning,but worth reading)**:star::star::star::star::star:
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**[60]** Koch, Gregory, Richard Zemel, and Ruslan Salakhutdinov. "**Siamese Neural Networks for One-shot Image Recognition**."(2015) [[pdf]](http://www.cs.utoronto.ca/~gkoch/files/msc-thesis.pdf):star::star::star:
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**[61]** Koch, Gregory, Richard Zemel, and Ruslan Salakhutdinov. "**Siamese Neural Networks for One-shot Image Recognition**."(2015) [[pdf]](http://www.cs.utoronto.ca/~gkoch/files/msc-thesis.pdf):star::star::star:
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**[61]** Santoro, Adam, et al. "**One-shot Learning with Memory-Augmented Neural Networks**." arXiv preprint arXiv:1605.06065 (2016). [[pdf]](http://arxiv.org/pdf/1605.06065)**(A basic step to one shot learning)**:star::star::star::star:
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**[62]** Santoro, Adam, et al. "**One-shot Learning with Memory-Augmented Neural Networks**." arXiv preprint arXiv:1605.06065 (2016). [[pdf]](http://arxiv.org/pdf/1605.06065)**(A basic step to one shot learning)**:star::star::star::star:
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**[62]** Vinyals, Oriol, et al. "**Matching Networks for One Shot Learning**." arXiv preprint arXiv:1606.04080 (2016). [[pdf]](https://arxiv.org/pdf/1606.04080):star::star::star:
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**[63]** Vinyals, Oriol, et al. "**Matching Networks for One Shot Learning**." arXiv preprint arXiv:1606.04080 (2016). [[pdf]](https://arxiv.org/pdf/1606.04080):star::star::star:
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**[63]** Hariharan, Bharath, and Ross Girshick. "**Low-shot visual object recognition**." arXiv preprint arXiv:1606.02819 (2016). [[pdf]](http://arxiv.org/pdf/1606.02819)**(A step to large data)**:star::star::star::star:
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**[64]** Hariharan, Bharath, and Ross Girshick. "**Low-shot visual object recognition**." arXiv preprint arXiv:1606.02819 (2016). [[pdf]](http://arxiv.org/pdf/1606.02819)**(A step to large data)**:star::star::star::star:
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