http://wiki.math.uwaterloo.ca/statwiki/api.php?action=feedcontributions&user=Yf3jiang&feedformat=atom
statwiki - User contributions [US]
2024-03-29T10:10:45Z
User contributions
MediaWiki 1.41.0
http://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat441F18&diff=39602
stat441F18
2018-11-17T06:17:36Z
<p>Yf3jiang: </p>
<hr />
<div><br />
<br />
== [[F18-STAT841-Proposal| Project Proposal ]] ==<br />
<br />
[https://goo.gl/forms/apurag4dr9kSR76X2 Your feedback on presentations]<br />
<br />
<br />
= Record your contributions here [https://docs.google.com/spreadsheets/d/10CHiJpAylR6kB9QLqN7lZHN79D9YEEW6CDTH27eAhbQ/edit?usp=sharing]=<br />
<br />
Use the following notations:<br />
<br />
P: You have written a summary/critique on the paper.<br />
<br />
T: You had a technical contribution on a paper (excluding the paper that you present).<br />
<br />
E: You had an editorial contribution on a paper (excluding the paper that you present).<br />
<br />
<br />
<br />
<br />
=Paper presentation=<br />
{| class="wikitable"<br />
<br />
{| border="1" cellpadding="3"<br />
|-<br />
|width="60pt"|Date<br />
|width="100pt"|Name <br />
|width="30pt"|Paper number <br />
|width="700pt"|Title<br />
|width="30pt"|Link to the paper<br />
|width="30pt"|Link to the summary<br />
|-<br />
|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]<br />
|-<br />
|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]<br />
|-<br />
|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]<br />
|-<br />
|NOv 15 || Yan Yu Chen, Qisi Deng, Hengxin Li, Bochao Zhang|| 3|| Topic Compositional Neural Language Model|| [https://arxiv.org/pdf/1712.09783.pdf paper] || <br />
[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat441F18/TCNLM Summary]<br />
|-<br />
|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|| [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6035797 Paper] || <br />
[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat841F18/ Summary]<br />
|-<br />
|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] <br />
|-<br />
|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] <br />
|-<br />
|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]<br />
|-<br />
|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]<br />
|-<br />
|NOv 27 || Mitchell Snaith || 9|| You Only Look Once: Unified, Real-Time Object Detection, V1 -> V3 || [https://arxiv.org/pdf/1506.02640.pdf Paper] || <br />
|-<br />
|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 || [https://arxiv.org/pdf/1707.02919.pdf Paper] || <br />
|-<br />
|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] || <br />
|-<br />
|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] ||<br />
|-<br />
|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] ||<br />
|-<br />
|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]<br />
|-<br />
|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]<br />
|-<br />
|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] ||</div>
Yf3jiang
http://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat441F18&diff=39601
stat441F18
2018-11-17T06:13:28Z
<p>Yf3jiang: </p>
<hr />
<div><br />
<br />
== [[F18-STAT841-Proposal| Project Proposal ]] ==<br />
<br />
[https://goo.gl/forms/apurag4dr9kSR76X2 Your feedback on presentations]<br />
<br />
<br />
= Record your contributions here [https://docs.google.com/spreadsheets/d/10CHiJpAylR6kB9QLqN7lZHN79D9YEEW6CDTH27eAhbQ/edit?usp=sharing]=<br />
<br />
Use the following notations:<br />
<br />
P: You have written a summary/critique on the paper.<br />
<br />
T: You had a technical contribution on a paper (excluding the paper that you present).<br />
<br />
E: You had an editorial contribution on a paper (excluding the paper that you present).<br />
<br />
<br />
<br />
<br />
=Paper presentation=<br />
{| class="wikitable"<br />
<br />
{| border="1" cellpadding="3"<br />
|-<br />
|width="60pt"|Date<br />
|width="100pt"|Name <br />
|width="30pt"|Paper number <br />
|width="700pt"|Title<br />
|width="30pt"|Link to the paper<br />
|width="30pt"|Link to the summary<br />
|-<br />
|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]<br />
|-<br />
|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] ||<br />
|-<br />
|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]<br />
|-<br />
|NOv 15 || Yan Yu Chen, Qisi Deng, Hengxin Li, Bochao Zhang|| 3|| Topic Compositional Neural Language Model|| [https://arxiv.org/pdf/1712.09783.pdf paper] || <br />
[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat441F18/TCNLM Summary]<br />
|-<br />
|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|| [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6035797 Paper] || <br />
[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat841F18/ Summary]<br />
|-<br />
|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] ||<br />
|-<br />
|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]|| <br />
|-<br />
|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]<br />
|-<br />
|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]<br />
|-<br />
|NOv 27 || Mitchell Snaith || 9|| You Only Look Once: Unified, Real-Time Object Detection, V1 -> V3 || [https://arxiv.org/pdf/1506.02640.pdf Paper] || <br />
|-<br />
|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 || [https://arxiv.org/pdf/1707.02919.pdf Paper] || <br />
|-<br />
|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] || <br />
|-<br />
|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 ||<br />
[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] <br />
|-<br />
|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] ||<br />
|-<br />
|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]<br />
|-<br />
|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]|<br />
|-<br />
|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] ||</div>
Yf3jiang
http://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat441F18&diff=39600
stat441F18
2018-11-17T06:12:13Z
<p>Yf3jiang: </p>
<hr />
<div><br />
<br />
== [[F18-STAT841-Proposal| Project Proposal ]] ==<br />
<br />
[https://goo.gl/forms/apurag4dr9kSR76X2 Your feedback on presentations]<br />
<br />
<br />
= Record your contributions here [https://docs.google.com/spreadsheets/d/10CHiJpAylR6kB9QLqN7lZHN79D9YEEW6CDTH27eAhbQ/edit?usp=sharing]=<br />
<br />
Use the following notations:<br />
<br />
P: You have written a summary/critique on the paper.<br />
<br />
T: You had a technical contribution on a paper (excluding the paper that you present).<br />
<br />
E: You had an editorial contribution on a paper (excluding the paper that you present).<br />
<br />
<br />
<br />
<br />
=Paper presentation=<br />
{| class="wikitable"<br />
<br />
{| border="1" cellpadding="3"<br />
|-<br />
|width="60pt"|Date<br />
|width="100pt"|Name <br />
|width="30pt"|Paper number <br />
|width="700pt"|Title<br />
|width="30pt"|Link to the paper<br />
|width="30pt"|Link to the summary<br />
|-<br />
|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]<br />
|-<br />
|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] ||<br />
|-<br />
|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]<br />
|-<br />
|NOv 15 || Yan Yu Chen, Qisi Deng, Hengxin Li, Bochao Zhang|| 3|| Topic Compositional Neural Language Model|| [https://arxiv.org/pdf/1712.09783.pdf paper] || <br />
[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat441F18/TCNLM Summary]<br />
|-<br />
|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|| [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6035797 Paper] || <br />
[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat841F18/ Summary]<br />
|-<br />
|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] ||<br />
|-<br />
|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]|| <br />
|-<br />
|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]<br />
|-<br />
|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]<br />
|-<br />
|NOv 27 || Mitchell Snaith || 9|| You Only Look Once: Unified, Real-Time Object Detection, V1 -> V3 || [https://arxiv.org/pdf/1506.02640.pdf Paper] || <br />
|-<br />
|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 || [https://arxiv.org/pdf/1707.02919.pdf Paper] || <br />
|-<br />
|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] || <br />
|-<br />
|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 ||<br />
[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] <br />
|-<br />
|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] ||<br />
|-<br />
|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]|<br />
|-<br />
|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]|<br />
|-<br />
|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] ||</div>
Yf3jiang
http://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat441F18&diff=39599
stat441F18
2018-11-17T06:11:45Z
<p>Yf3jiang: </p>
<hr />
<div><br />
<br />
== [[F18-STAT841-Proposal| Project Proposal ]] ==<br />
<br />
[https://goo.gl/forms/apurag4dr9kSR76X2 Your feedback on presentations]<br />
<br />
<br />
= Record your contributions here [https://docs.google.com/spreadsheets/d/10CHiJpAylR6kB9QLqN7lZHN79D9YEEW6CDTH27eAhbQ/edit?usp=sharing]=<br />
<br />
Use the following notations:<br />
<br />
P: You have written a summary/critique on the paper.<br />
<br />
T: You had a technical contribution on a paper (excluding the paper that you present).<br />
<br />
E: You had an editorial contribution on a paper (excluding the paper that you present).<br />
<br />
<br />
<br />
<br />
=Paper presentation=<br />
{| class="wikitable"<br />
<br />
{| border="1" cellpadding="3"<br />
|-<br />
|width="60pt"|Date<br />
|width="100pt"|Name <br />
|width="30pt"|Paper number <br />
|width="700pt"|Title<br />
|width="30pt"|Link to the paper<br />
|width="30pt"|Link to the summary<br />
|-<br />
|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]<br />
|-<br />
|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] ||<br />
|-<br />
|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]<br />
|-<br />
|NOv 15 || Yan Yu Chen, Qisi Deng, Hengxin Li, Bochao Zhang|| 3|| Topic Compositional Neural Language Model|| [https://arxiv.org/pdf/1712.09783.pdf paper] || <br />
[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat441F18/TCNLM Summary]<br />
|-<br />
|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|| [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6035797 Paper] || <br />
[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=stat841F18/ Summary]<br />
|-<br />
|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] ||<br />
|-<br />
|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]|| <br />
|-<br />
|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]<br />
|-<br />
|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]<br />
|-<br />
|NOv 27 || Mitchell Snaith || 9|| You Only Look Once: Unified, Real-Time Object Detection, V1 -> V3 || [https://arxiv.org/pdf/1506.02640.pdf Paper] || <br />
|-<br />
|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 || [https://arxiv.org/pdf/1707.02919.pdf Paper] || <br />
|-<br />
|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] || <br />
|-<br />
|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 ||<br />
[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] <br />
|-<br />
|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] ||<br />
|-<br />
|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]|<br />
|-<br />
|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]<br />
|-<br />
|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] ||</div>
Yf3jiang
http://wiki.math.uwaterloo.ca/statwiki/index.php?title=Representations_of_Words_and_Phrases_and_their_Compositionality&diff=39598
Representations of Words and Phrases and their Compositionality
2018-11-17T06:10:30Z
<p>Yf3jiang: Created page with "Hello World!"</p>
<hr />
<div>Hello World!</div>
Yf3jiang