stat441F18: Difference between revisions
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|Feb 15 (example)||Ri Wang || ||Sequence to sequence learning with neural networks.||[http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf Paper] || [http://wikicoursenote.com/wiki/Stat946f15/Sequence_to_sequence_learning_with_neural_networks#Long_Short-Term_Memory_Recurrent_Neural_Network Summary] | |Feb 15 (example)||Ri Wang || ||Sequence to sequence learning with neural networks.||[http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf Paper] || [http://wikicoursenote.com/wiki/Stat946f15/Sequence_to_sequence_learning_with_neural_networks#Long_Short-Term_Memory_Recurrent_Neural_Network Summary] | ||
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|Nov 13 || | |Nov 13 || || 1|| || || | ||
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|Nov 13 ||Sai Praneeth M, Xudong Peng, Alice Li, Shahrzad Hosseini Vajargah|| 2|| Going Deeper with Convolutions ||[https://arxiv.org/pdf/1409.4842.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Going_Deeper_with_Convolutions Summary] | |Nov 13 ||Sai Praneeth M, Xudong Peng, Alice Li, Shahrzad Hosseini Vajargah|| 2|| Going Deeper with Convolutions ||[https://arxiv.org/pdf/1409.4842.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Going_Deeper_with_Convolutions Summary] | ||
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|Nov 22 || Hanzhen Yang, Jing Pu Sun, Ganyuan Xuan, Yu Su, Jiacheng Weng, Keqi Li, Yi Qian, Bomeng Liu || 8|| Deep Residual Learning for Image Recognition || [http://openaccess.thecvf.com/content_cvpr_2016/papers/He_Deep_Residual_Learning_CVPR_2016_paper.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Deep_Residual_Learning_for_Image_Recognition Summary] | |Nov 22 || Hanzhen Yang, Jing Pu Sun, Ganyuan Xuan, Yu Su, Jiacheng Weng, Keqi Li, Yi Qian, Bomeng Liu || 8|| Deep Residual Learning for Image Recognition || [http://openaccess.thecvf.com/content_cvpr_2016/papers/He_Deep_Residual_Learning_CVPR_2016_paper.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Deep_Residual_Learning_for_Image_Recognition Summary] | ||
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|NOv 27 || Mitchell Snaith || 9|| You Only Look Once: Unified, Real-Time Object Detection | |NOv 27 || Mitchell Snaith || 9|| You Only Look Once: Unified, Real-Time Object Detection || [https://arxiv.org/pdf/1506.02640.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat441F18/YOLO Summary] | ||
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|Nov 27 || Qi Chu, | |Nov 27 || Qi Chu, Xiaoran Huang, Di Sang, Amanda Lam, Yan Jiao, Shuyue Wang, Yutong Wu || 10|| A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques || [https://arxiv.org/pdf/1707.02919.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=A_Brief_Survey_of_Text_Mining:_Classification,_Clustering_and_Extraction_Techniques Summary] | ||
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|NOv 29 || Jameson Ngo, Amy Xu, Aden Grant, Yu Hao Wang, Andrew McMurry, Baizhi Song, Yongqi Dong || 11|| Towards Deep Learning Models Resistant to Adversarial Attacks || [https:// | |NOv 29 || Jameson Ngo, Amy Xu, Aden Grant, Yu Hao Wang, Andrew McMurry, Baizhi Song, Yongqi Dong || 11|| Towards Deep Learning Models Resistant to Adversarial Attacks || [https://openreview.net/pdf?id=rJzIBfZAb Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Towards_Deep_Learning_Models_Resistant_to_Adversarial_Attacks Summary] | ||
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|Nov 29 || Qianying Zhao, Hui Huang, Lingyun Yi, Jiayue Zhang, Siao Chen, Rongrong Su, Gezhou Zhang, Meiyu Zhou || 12|| XGBoost: A Scalable Tree Boosting System || [ | |Nov 29 || Qianying Zhao, Hui Huang, Lingyun Yi, Jiayue Zhang, Siao Chen, Rongrong Su, Gezhou Zhang, Meiyu Zhou || 12|| XGBoost: A Scalable Tree Boosting System || [https://wiki.math.uwaterloo.ca/statwiki/images/9/9f/paper_presentation.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=XGBoost:_A_Scalable_Tree_Boosting_System Summary] | ||
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|Nov 28 || Hudson Ash, Stephen Kingston, Richard Zhang, Alexandre Xiao, Ziqiu Zhu || 13 || Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness || [https://arxiv.org/pdf/1608.05842.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Unsupervised_Learning_of_Optical_Flow_via_Brightness_Constancy_and_Motion_Smoothness Summary] | |Nov 28 || Hudson Ash, Stephen Kingston, Richard Zhang, Alexandre Xiao, Ziqiu Zhu || 13 || Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness || [https://arxiv.org/pdf/1608.05842.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Unsupervised_Learning_of_Optical_Flow_via_Brightness_Constancy_and_Motion_Smoothness Summary] | ||
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|Nov 21 || Frank Jiang, Yuan Zhang, Jerry Hu || 14 || Distributed Representations of Words and Phrases and their Compositionality || [https://arxiv.org/pdf/1310.4546.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Representations_of_Words_and_Phrases_and_their_Compositionality Summary] | |Nov 21 || Frank Jiang, Yuan Zhang, Jerry Hu || 14 || Distributed Representations of Words and Phrases and their Compositionality || [https://arxiv.org/pdf/1310.4546.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Representations_of_Words_and_Phrases_and_their_Compositionality Summary] | ||
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|Nov 21 || Yu Xuan Lee, Tsen Yee Heng || 15 || Gradient Episodic Memory for Continual Learning || [http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf Paper] || | |Nov 21 || Yu Xuan Lee, Tsen Yee Heng || 15 || Gradient Episodic Memory for Continual Learning || [http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Gradient_Episodic_Memory_for_Continual_Learning Summary] | ||
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|Nov 28 || Ben Zhang, Rees Simmons, Sunil Mall || 16 || Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift || [https://arxiv.org/pdf/1502.03167.pdf Paper] || | |Nov 28 || Ben Zhang, Rees Simmons, Sunil Mall || 16 || Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift || [https://arxiv.org/pdf/1502.03167.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Batch_Normalization Summary] | ||
Latest revision as of 10:33, 5 September 2020
Project Proposal
Your feedback on presentations
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 |
| Feb 15 (example) | Ri Wang | Sequence to sequence learning with neural networks. | Paper | Summary | |
| Nov 13 | 1 | ||||
| Nov 13 | Sai Praneeth M, Xudong Peng, Alice Li, Shahrzad Hosseini Vajargah | 2 | Going Deeper with Convolutions | Paper | Summary |
| NOv 15 | Yan Yu Chen, Qisi Deng, Hengxin Li, Bochao Zhang | 3 | Topic Compositional Neural Language Model | paper | |
| Nov 15 | Zhaoran Hou, Pei Wei Wang, Chi Zhang, Yiming Li, Daoyi Chen, Ying Chi | 4 | Extreme Learning Machine for regression and Multi-class Classification | Paper | |
| NOv 20 | Kristi Brewster, Isaac McLellan, Ahmad Nayar Hassan, Marina Medhat Rassmi Melek, Brendan Ross, Jon Barenboim, Junqiao Lin, James Bootsma | 5 | A Neural Representation of Sketch Drawings | Paper | Summary |
| Nov 20 | Maya(Mahdiyeh) Bayati, Saber Malekmohammadi, Vincent Loung | 6 | Convolutional Neural Networks for Sentence Classification | paper | Summary |
| NOv 22 | Qingxi Huo, Yanmin Yang, Jiaqi Wang, Yuanjing Cai, Colin Stranc, Philomène Bobichon, Aditya Maheshwari, Zepeng An | 7 | Robust Probabilistic Modeling with Bayesian Data Reweighting | Paper | Summary |
| Nov 22 | Hanzhen Yang, Jing Pu Sun, Ganyuan Xuan, Yu Su, Jiacheng Weng, Keqi Li, Yi Qian, Bomeng Liu | 8 | Deep Residual Learning for Image Recognition | Paper | Summary |
| NOv 27 | Mitchell Snaith | 9 | You Only Look Once: Unified, Real-Time Object Detection | Paper | Summary |
| Nov 27 | Qi Chu, Xiaoran Huang, Di Sang, Amanda Lam, Yan Jiao, Shuyue Wang, Yutong Wu | 10 | A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques | Paper | Summary |
| NOv 29 | Jameson Ngo, Amy Xu, Aden Grant, Yu Hao Wang, Andrew McMurry, Baizhi Song, Yongqi Dong | 11 | Towards Deep Learning Models Resistant to Adversarial Attacks | Paper | Summary |
| Nov 29 | Qianying Zhao, Hui Huang, Lingyun Yi, Jiayue Zhang, Siao Chen, Rongrong Su, Gezhou Zhang, Meiyu Zhou | 12 | XGBoost: A Scalable Tree Boosting System | Paper | Summary |
| Nov 28 | Hudson Ash, Stephen Kingston, Richard Zhang, Alexandre Xiao, Ziqiu Zhu | 13 | Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness | Paper | Summary |
| Nov 21 | Frank Jiang, Yuan Zhang, Jerry Hu | 14 | Distributed Representations of Words and Phrases and their Compositionality | Paper | Summary |
| Nov 21 | Yu Xuan Lee, Tsen Yee Heng | 15 | Gradient Episodic Memory for Continual Learning | Paper | Summary |
| Nov 28 | Ben Zhang, Rees Simmons, Sunil Mall | 16 | Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift | Paper | Summary |