# Difference between revisions of "stat940F21"

From statwiki

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|Week of Nov 23 || Mohan Wu || 21|| Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Cluster for Extreme Multi-label Text Classification || [https://proceedings.icml.cc/static/paper_files/icml/2020/807-Paper.pdf Paper] || || | |Week of Nov 23 || Mohan Wu || 21|| Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Cluster for Extreme Multi-label Text Classification || [https://proceedings.icml.cc/static/paper_files/icml/2020/807-Paper.pdf Paper] || || | ||

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− | |Week of Nov 23 || Xinyi Yan || 22|| Dense Passage Retrieval for Open-Domain Question Answering || [https://arxiv.org/abs/2004.04906 Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Dense_Passage_Retrieval_for_Open-Domain_Question_Answering Summary] || | + | |Week of Nov 23 || Xinyi Yan || 22|| Dense Passage Retrieval for Open-Domain Question Answering || [https://arxiv.org/abs/2004.04906 Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Dense_Passage_Retrieval_for_Open-Domain_Question_Answering Summary] || Learn |

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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] || || |

## Revision as of 22:48, 18 November 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 | Jose Avilez | 1 | Gradientless Descent: High-Dimensional Zeroth-Order Optimisation | [3] | GradientLess Descent | GLD Presentation File:GradientLessDescent.pdf | |

Week of Nov 2 | Abhinav Chanana | 2 | AUGMIX: A Simple Data Procession method to Improve Robustness And Uncertainity | Paper | Summary | [Presentation ] | |

Week of Nov 2 | Maziar Dadbin | 3 | ALBERT: A Lite BERT for Self-supervised Learning of Language Representations | paper | Summary | ||

Week of Nov 2 | John Landon Edwards | 4 | From Variational to Deterministic Autoencoders | Paper | Summary | Presentation | |

Week of Nov 2 | Wenyu Shen | 5 | Pre-training of Deep Bidirectional Transformers for Language Understanding | Paper | Summary | Presentation video | |

Week of Nov 2 | Syed Saad Naseem | 6 | Learning The Difference That Makes A Difference With Counterfactually-Augmented Data | Paper | Summary | Presentation video | |

Week of Nov 9 | Donya Hamzeian | 7 | The Curious Case of Neural Text Degeneration | Paper | Summary | ||

Week of Nov 9 | Parsa Torabian | 8 | Orthogonal Gradient Descent for Continual Learning | Paper | Summary | Learn | |

Week of Nov 9 | Arash Moayyedi | 9 | When Does Self-supervision Improve Few-shot Learning? | Paper | Summary | Learn | |

Week of Nov 9 | Parsa Ashrafi Fashi | 10 | Learning to Generalize: Meta-Learning for Domain Generalization | Paper | Summary | Presentation Video | |

Week of Nov 9 | Jaskirat Singh Bhatia | 11 | A FAIRCOMPARISON OFGRAPHNEURALNETWORKSFORGRAPHCLASSIFICATION | Paper | Summary | Presentation | |

Week of Nov 9 | Gaurav Sikri | 12 | BREAKING CERTIFIED DEFENSES: SEMANTIC ADVERSARIAL EXAMPLES WITH SPOOFED ROBUSTNESS CERTIFICATES | Paper | Summary | [Presentation ] | |

Week of Nov 16 | Abhinav Jain | 13 | The Logical Expressiveness of Graph Neural Networks | Paper | |||

Week of Nov 16 | Gautam Bathla | 14 | One-Shot Object Detection with Co-Attention and Co-Excitation | Paper | |||

Week of Nov 16 | Shikhar Sakhuja | 15 | SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems | Paper | Summary | [Presentation ] | |

Week of Nov 16 | Cameron Meaney | 16 | Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations | Paper | Summary | Learn | |

Week of Nov 16 | Sobhan Hemati | 17 | Adversarial Fisher Vectors for Unsupervised Representation Learning | Paper | Summary | video | |

Week of Nov 16 | Milad Sikaroudi | 18 | Domain Genralization via Model Agnostic Learning of Semantic Features | Paper | Summary | video also available on Learn | |

Week of Nov 23 | Bowen You | 19 | DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION | Paper | Summary | ||

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 | Dense Passage Retrieval for Open-Domain Question Answering | Paper | Summary | Learn | |

Week of Nov 23 | Meixi Chen | 23 | Functional Regularisation for Continual Learning with Gaussian Processes | Paper | |||

Week of Nov 23 | Ahmed Salamah | 24 | AdaCompress: Adaptive Compression for Online Computer Vision Services | Paper | Summary | ||

Week of Nov 23 | Mohammad Mahmoud | 32 | Mathematical Reasoning in Latent Space | [4] | |||

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 CLOSER LOOK AT FEW-SHOT CLASSIFICATION | https://arxiv.org/pdf/1904.04232.pdf | |||

Week of Nov 30 | Pierre McWhannel | 30 | Pre-training Tasks for Embedding-based Large-scale Retrieval | Paper | Do Not Review Yet | Learn | |

Week of Nov 30 | Wenjuan Qi | 31 | Network Deconvolution | Paper | placeholder |