Difference between revisions of "Winter 2021 CS291A Syllabus"

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*01/4 Introduction, logistics, and deep learning.
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Checkout the class presentation schedule for additional readings:
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*01/6 Tips for a successful class project
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[https://docs.google.com/spreadsheets/d/1p0M7X9OZwcRHT4OhxX3snGjskfltUG-uFIL0T6rLjK8/edit?usp=sharing Class Presentation Schedule]
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*01/11 Neural network basics, & backpropagation  
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*01/13 Word embeddings (Project proposal due [https://forms.gle/TjYSjc5iE1Zm24ED8 submission link], HW1 out)
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*1/4 Introduction, logistics, and deep learning.
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*01/18 University Holiday: Martin Luther King Jr. Day
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*1/6 Tips for a successful class project
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*01/20 RNNs
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*1/11 Neural network basics, & backpropagation  
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*01/25 LSTMs/GRUs
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*1/13 Word embeddings (Project proposal due 23:59PT 1/13 [https://forms.gle/TjYSjc5iE1Zm24ED8 submission link], HW1 out)
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*01/27 Sequence-to-sequence models
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** [https://www.aclweb.org/anthology/Q17-1010/ Enriching Word Vectors with Subword Information]
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*02/1 Convolutional Neural Networks (HW1 due and HW2 out)
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** [https://www.aclweb.org/anthology/C18-1139/ Contextual String Embeddings for Sequence Labeling]
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*02/3 Attention mechanisms
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*1/18 NO CLASS (University Holiday: Martin Luther King Jr. Day)
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*02/8 Transformer and BERT (Mid-term report due [https://forms.gle/3mLA46FANTDZ5s5FA submission link])
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*1/20 RNNs
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*02/10 BERT (continued)
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** [http://www.fit.vutbr.cz/research/groups/speech/publi/2010/mikolov_interspeech2010_IS100722.pdf Recurrent neural network based language model]
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*02/15 University Holiday: Presidents' Day
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** [https://arxiv.org/abs/1502.03240 Conditional Random Fields as Recurrent Neural Networks]
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*02/17 Language and vision
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*1/25 LSTMs/GRUs
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**[https://openreview.net/pdf?id=YicbFdNTTy An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale]
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** [https://arxiv.org/pdf/1802.05365.pdf Deep contextualized word representations]
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*02/22 Deep Reinforcement Learning 1 (HW2 due: 02/26 Monday 11:59pm)
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** [https://arxiv.org/pdf/1410.3916.pdf Memory Networks]
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*02/24 Deep Reinforcement Learning 2
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*1/27 Sequence-to-sequence models
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*03/1 Generative Adversarial Networks
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** [https://www.aclweb.org/anthology/N19-4009/ fairseq: A Fast, Extensible Toolkit for Sequence Modeling]
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** [https://arxiv.org/abs/1511.06732 Sequence Level Training with Recurrent Neural Networks]
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*2/1 Convolutional Neural Networks (HW1 due and HW2 out)
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** [https://arxiv.org/abs/1608.06993 Densely Connected Convolutional Networks]
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** [https://www.nature.com/articles/s41586-019-1923-7 Improved protein structure prediction using potentials from deep learning]
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*2/3 Attention mechanisms
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** [https://www.aclweb.org/anthology/D15-1044.pdf A Neural Attention Model for Sentence Summarization]
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** [https://arxiv.org/abs/1409.0473 Neural Machine Translation by Jointly Learning to Align and Translate]
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*2/8 Transformer and BERT (Mid-term report due [https://forms.gle/3mLA46FANTDZ5s5FA submission link])
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** [https://arxiv.org/abs/1906.08237 XLNet: Generalized Autoregressive Pretraining for Language Understanding]
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** [https://arxiv.org/abs/1907.11692 RoBERTa: A Robustly Optimized BERT Pretraining Approach]
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** [https://arxiv.org/abs/1909.11942 ALBERT: A Lite BERT for Self-supervised Learning of Language Representations]
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*2/10 Mid-term project updates [https://forms.gle/XMKr1nNsJieUK4jD6 upload your slide here] by 2/9 noon
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*2/15 NO CLASS (University Holiday: Presidents' Day)
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*2/17 Language and vision
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** [https://openreview.net/pdf?id=YicbFdNTTy An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale]
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** [https://openaccess.thecvf.com/content_CVPR_2020/papers/Chaplot_Neural_Topological_SLAM_for_Visual_Navigation_CVPR_2020_paper.pdf Neural Topological SLAM for Visual Navigation]
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*2/22 Deep Reinforcement Learning 1  
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** [https://papers.nips.cc/paper/2017/hash/9e82757e9a1c12cb710ad680db11f6f1-Abstract.html Imagination-Augmented Agents for Deep Reinforcement Learning]
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** [https://openreview.net/pdf?id=S1g2skStPB Causal Discovery with Reinforcement Learning]
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*2/24 Deep Reinforcement Learning 2 (HW2 due: 02/26 Friday 11:59pm)
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** [https://arxiv.org/abs/1705.05363 Curiosity-driven Exploration by Self-supervised Prediction]
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** [https://www.nature.com/articles/s41586-019-1724-z Grandmaster level in StarCraft II using multi-agent reinforcement learning]
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** [https://www.nature.com/articles/s41586-020-03051-4 Mastering Atari, Go, chess and shogi by planning with a learned model]
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*3/1 Generative Adversarial Networks
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** [https://arxiv.org/abs/1701.04862 Towards Principled Methods for Training Generative Adversarial Networks]
 
** [https://arxiv.org/abs/1701.07875 Wasserstein GAN]
 
** [https://arxiv.org/abs/1701.07875 Wasserstein GAN]
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*03/3 Project: final presentation (1)
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** [https://arxiv.org/abs/1703.10717 Boundary Equilibrium GAN]
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*03/8 Project: final presentation (2)
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* Check out final project presentation schedule here: [https://docs.google.com/spreadsheets/d/1T791ZMd4l6IZrdcWhpTuZx-37f_XWEgfd_BtGmEXRrw/edit?usp=sharing schedule]
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*03/10 Project: final presentation (3)
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*3/3 Project: final presentation (1) [https://forms.gle/7d2iVhT322bzY9UCA submission link] by 3/2 noon.
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*03/19 23:59PM PT Project Final Report Due [https://forms.gle/kgN8n8XDz83NWdxo9 submission link].
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*3/8 Project: final presentation (2) [https://forms.gle/7d2iVhT322bzY9UCA submission link] by 3/7 noon.
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*3/10 Project: final presentation (3) [https://forms.gle/7d2iVhT322bzY9UCA submission link] by 3/9 noon.
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*3/19 23:59PM PT Project Final Report Due [https://forms.gle/kgN8n8XDz83NWdxo9 submission link].

Latest revision as of 21:56, 21 February 2021

Checkout the class presentation schedule for additional readings: Class Presentation Schedule

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