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|Week of Nov 23 ||Guanting Pan, Haocheng Chang, Zaiwei Zhang || 18|| Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence || [https://arxiv.org/pdf/1809.10770.pdf Paper] || || | |Week of Nov 23 ||Guanting Pan, Haocheng Chang, Zaiwei Zhang || 18|| Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence || [https://arxiv.org/pdf/1809.10770.pdf Paper] || || | ||
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|Week of Nov 23 || Jerry Huang, Daniel Jiang, Minyan Dai, Leyan Cheng || 19|| Neural Speed Reading Via Skim-RNN ||[https://arxiv.org/pdf/1711.02085.pdf?fbclid=IwAR3EeFsKM_b5p9Ox7X9mH-1oI3U3oOKPBy3xUOBN0XvJa7QW2ZeJJ9ypQVo] | |Week of Nov 23 || Jerry Huang, Daniel Jiang, Minyan Dai, Leyan Cheng || 19|| Neural Speed Reading Via Skim-RNN ||[https://arxiv.org/pdf/1711.02085.pdf?fbclid=IwAR3EeFsKM_b5p9Ox7X9mH-1oI3U3oOKPBy3xUOBN0XvJa7QW2ZeJJ9ypQVo Paper] || || | ||
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|Week of Nov 23 ||Ruixian Chin, Yan Kai Tan, Jason Ong, Wen Cheen Chiew || 20|| DivideMix: Learning with Noisy Labels as Semi-supervised Learning || [https://openreview.net/pdf?id=HJgExaVtwr] || || | |Week of Nov 23 ||Ruixian Chin, Yan Kai Tan, Jason Ong, Wen Cheen Chiew || 20|| DivideMix: Learning with Noisy Labels as Semi-supervised Learning || [https://openreview.net/pdf?id=HJgExaVtwr] || || |
Revision as of 23:26, 6 October 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 16 | Sharman Bharat, Li Dylan,Lu Leonie, Li Mingdao | 1 | Risk prediction in life insurance industry using supervised learning algorithms | Paper | Summary | |
Week of Nov 16 | Delaney Smith, Mohammad Assem Mahmoud | 2 | Influenza Forecasting Framework based on Gaussian Processes | [3] paper | ||
Week of Nov 16 | Tatianna Krikella, Swaleh Hussain, Grace Tompkins | 3 | Processing of Missing Data by Neural Networks | [4] | ||
Week of Nov 16 | Jonathan Chow, Nyle Dharani, Ildar Nasirov | 4 | Streaming Bayesian Inference for Crowdsourced Classification | Paper | ||
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Week of Nov 23 | Jinjiang Lian, Jiawen Hou, Yisheng Zhu, Mingzhe Huang | 11 | DROCC: Deep Robust One-Class Classification | paper | ||
Week of Nov 23 | Bushra Haque, Hayden Jones, Michael Leung, Cristian Mustatea | 12 | Combine Convolution with Recurrent Netorks for Text Classification | Paper | ||
Week of Nov 23 | 13 | |||||
Week of Nov 23 | Qianlin Song, William Loh, Junyue Bai, Phoebe Choi | 14 | Task Understanding from Confusing Multi-task Data | paper | ||
Week of Nov 23 | 15 | |||||
Week of Nov 23 | Xiaolan Xu, Robin Wen, Yue Weng, Beizhen Chang | 16 | ||||
Week of Nov 23 | Hansa Halim, Sanjana Rajendra Naik, Samka Marfua, Shawrupa Proshasty | 17 | Emergent Tool Use From Multi-Agent Autocurricula | [5] | ||
Week of Nov 23 | Guanting Pan, Haocheng Chang, Zaiwei Zhang | 18 | Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence | Paper | ||
Week of Nov 23 | Jerry Huang, Daniel Jiang, Minyan Dai, Leyan Cheng | 19 | Neural Speed Reading Via Skim-RNN | Paper | ||
Week of Nov 23 | Ruixian Chin, Yan Kai Tan, Jason Ong, Wen Cheen Chiew | 20 | DivideMix: Learning with Noisy Labels as Semi-supervised Learning | [6] | ||
Week of Nov 30 | 21 | |||||
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Week of Nov 30 | Anas Mahdi Will Thibault Jan Lau Jiwon Yang | 25 | Loss Function Search for Face Recognition | [7] paper | ||
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Week of Nov 30 | Bertrand Sodjahin, Junyi Yang, Jill Yu Chieh Wang, Yu Min Wu, Calvin Li | 30 | Research paper classifcation systems based on TF‑IDF and LDA schemes | Paper |