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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 || Jason Schneider, Jordyn Walton, Zahraa Abbas, Andrew Na  || 1|| Memory-Based Parameter Adaptation ||  [https://arxiv.org/pdf/1802.10542.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Memory-Based_Parameter_Adaptation#Incremental_Learning Summary] ||
|Nov 13 || Jason Schneider, Jordyn Walton, Zahraa Abbas, Andrew Na  || 1|| Memory-Based Parameter Adaptation ||  [https://arxiv.org/pdf/1802.10542.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Memory-Based_Parameter_Adaptation#Incremental_Learning Summary]
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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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[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat841F18/ Summary]
[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat841F18/ Summary]
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|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 || [https://arxiv.org/pdf/1704.03477.pdf Paper]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Summary_-_A_Neural_Representation_of_Sketch_Drawings Summary] ||
|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 || [https://arxiv.org/pdf/1704.03477.pdf Paper]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Summary_-_A_Neural_Representation_of_Sketch_Drawings Summary]  
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|Nov 20 || Maya(Mahdiyeh) Bayati, Saber Malekmohammadi, Vincent Loung || 6|| Convolutional Neural Networks for Sentence Classification || [https://arxiv.org/pdf/1408.5882.pdf paper] ||  [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Convolutional_Neural_Networks_for_Sentence_Classi%EF%AC%81cation summary]||
|Nov 20 || Maya(Mahdiyeh) Bayati, Saber Malekmohammadi, Vincent Loung || 6|| Convolutional Neural Networks for Sentence Classification || [https://arxiv.org/pdf/1408.5882.pdf paper] ||  [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Convolutional_Neural_Networks_for_Sentence_Classi%EF%AC%81cation Summary]  
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|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 || [http://proceedings.mlr.press/v70/wang17g/wang17g.pdf Paper]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Robust_Probabilistic_Modeling_with_Bayesian_Data_Reweighting 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 || [http://proceedings.mlr.press/v70/wang17g/wang17g.pdf Paper]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Robust_Probabilistic_Modeling_with_Bayesian_Data_Reweighting 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://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|| 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 || [http://delivery.acm.org/10.1145/2940000/2939785/p785-chen.pdf?ip=129.97.124.2&id=2939785&acc=CHORUS&key=FD0067F557510FFB%2E9219CF56F73DCF78%2E4D4702B0C3E38B35%2E6D218144511F3437&__acm__=1542321481_ffea42f38a2b3325af4990280553c10f Paper] ||
[http://delivery.acm.org/10.1145/2940000/2939785/p785-chen.pdf?ip=129.97.124.2&id=2939785&acc=CHORUS&key=FD0067F557510FFB%2E9219CF56F73DCF78%2E4D4702B0C3E38B35%2E6D218144511F3437&__acm__=1542321481_ffea42f38a2b3325af4990280553c10f]  
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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] ||
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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]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Gradient_Episodic_Memory_for_Continual_Learning Summary]|
|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] ||

Revision as of 02:17, 17 November 2018


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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

Summary

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

Summary

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 A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques 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 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 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 Paper
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