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|Week of Nov 23 || Meixi Chen  || 23|| Functional Regularisation for Continual Learning with Gaussian Processes || [https://arxiv.org/pdf/1901.11356.pdf Paper]  || ||
|Week of Nov 23 || Meixi Chen  || 23|| Functional Regularisation for Continual Learning with Gaussian Processes || [https://arxiv.org/pdf/1901.11356.pdf Paper]  || ||
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|Week of Nov 23 || Ahmed Salamah  || 24|| Sparse Convolutional Neural Networks || https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Liu_Sparse_Convolutional_Neural_2015_CVPR_paper.pdf  || ||
|Week of Nov 23 || Ahmed Salamah  || 24|| Sparse Convolutional Neural Networks || [https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Liu_Sparse_Convolutional_Neural_2015_CVPR_paper.pdf] || ||
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|Week of Nov 30 ||Danial Maleki  || 25||Attention Is All You Need  ||[https://arxiv.org/abs/1706.03762 Paper]  || ||
|Week of Nov 30 ||Danial Maleki  || 25||Attention Is All You Need  ||[https://arxiv.org/abs/1706.03762 Paper]  || ||
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|Week of Nov 30 ||Maral Rasoolijaberi|| 28||Parameter-free, Dynamic, and Strongly-Adaptive Online Learning|| [https://proceedings.icml.cc/static/paper_files/icml/2020/2820-Paper.pdf Paper]  || ||
|Week of Nov 30 ||Maral Rasoolijaberi|| 28||Parameter-free, Dynamic, and Strongly-Adaptive Online Learning|| [https://proceedings.icml.cc/static/paper_files/icml/2020/2820-Paper.pdf Paper]  || ||
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|Week of Nov 30 || Sina Farsangi || 29|| A Baseline for Few-Shot Image Classification  ||  https://openreview.net/pdf?id=rylXBkrYDS || ||
|Week of Nov 30 || Sina Farsangi || 29|| A Baseline for Few-Shot Image Classification  ||  [https://openreview.net/pdf?id=rylXBkrYDS] || ||
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|Week of Nov 30 || Pierre McWhannel || 30|| Pre-training Tasks for Embedding-based Large-scale Retrieval || https://iclr.cc/virtual_2020/poster_rkg-mA4FDr.html  || placeholder||
|Week of Nov 30 || Pierre McWhannel || 30|| [Pre-training Tasks for Embedding-based Large-scale Retrieval || https://iclr.cc/virtual_2020/poster_rkg-mA4FDr.html] || placeholder||
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Revision as of 13:52, 6 October 2020

Project Proposal

Record your contributions here [1]

Use the following notations:

P: You have written a summary/critique on the paper.

T: You had a technical contribution on a paper (excluding the paper that you present).

E: You had an editorial contribution on a paper (excluding the paper that you present).


Paper presentation

Date Name Paper number Title Link to the paper Link to the summary Link to the video
Sep 15 (example) Ri Wang Sequence to sequence learning with neural networks. Paper Summary [2]
Week of Nov 2 1
Week of Nov 2 2
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Week of Nov 2 6
Week of Nov 9 7
Week of Nov 9 8
Week of Nov 9 9
Week of Nov 9 10
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Week of Nov 16 13
Week of Nov 16 14
Week of Nov 16 15
Week of Nov 16 16
Week of Nov 16 17
Week of Nov 16 18
Week of Nov 23 19
Week of Nov 23 Nouha Chatti 20 This Looks Like That: Deep Learning for Interpretable Image Recognition Paper
Week of Nov 23 Mohan Wu 21 Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Cluster for Extreme Multi-label Text Classification Paper
Week of Nov 23 Xinyi Yan 22 Incorporating BERT into Neural Machine Translation Paper
Week of Nov 23 Meixi Chen 23 Functional Regularisation for Continual Learning with Gaussian Processes Paper
Week of Nov 23 Ahmed Salamah 24 Sparse Convolutional Neural Networks [3]
Week of Nov 30 Danial Maleki 25 Attention Is All You Need Paper
Week of Nov 30 Gursimran Singh 26 BERTScore: Evaluating Text Generation with BERT. Paper
Week of Nov 30 Govind Sharma 27 Time-series Generative Adversarial Networks Paper
Week of Nov 30 Maral Rasoolijaberi 28 Parameter-free, Dynamic, and Strongly-Adaptive Online Learning Paper
Week of Nov 30 Sina Farsangi 29 A Baseline for Few-Shot Image Classification [4]
Week of Nov 30 Pierre McWhannel 30 [Pre-training Tasks for Embedding-based Large-scale Retrieval https://iclr.cc/virtual_2020/poster_rkg-mA4FDr.html] placeholder