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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://arxiv.org/pdf/1706.06083.pdf Paper] || | |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://arxiv.org/pdf/1706.06083.pdf Paper] || | ||
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|Nov 29 || Qianying Zhao, Hui Huang, Lingyun Yi, Jiayue Zhang, Siao Chen, Rongrong Su, Gezhou Zhang, Meiyu Zhou || 12|| || | |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://dl.acm.org/citation.cfm?id=2939785] || | |||
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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] || | |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] || |
Revision as of 17:30, 15 November 2018
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 | Jason Schneider, Jordyn Walton, Zahraa Abbas, Andrew Na | 1 | Memory-Based Parameter Adaptation | Paper | Summary | |
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, V1 -> V3 | Paper | ||
Nov 27 | Qi Chu, Gloria Huang, Dylan Sang, Amanda Lam, Yan Jiao, Shuyue Wang, Yutong Wu, Shikun Cui | 10 | tba | |||
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 | ||
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 |
[2] || | ||
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 | ||
Nov 21 | Frank Jiang, Yuan Zhang, Jerry Hu | 14 | Distributed Representations of Words and Phrases and their Compositionality | Paper | ||
Nov 21 | Yu Xuan Lee, Tsen Yee Heng | 15 | Gradient Episodic Memory for Continual Learning | Paper | ||
Nov 28 | Ben Zhang, Rees Simmons, Sunil Mall | 16 | Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift | Paper |