stat441F21
Project Proposal
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 | [1] | |
Week of Nov 16 | Ali Ghodsi | |||||
Week of Nov 22 | Jared Feng, Xipeng Huang, Mingwei Xu, Tingzhou Yu | Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification | Paper | Summary | ||
Week of Nov 29 | Kanika Chopra, Yush Rajcoomar | Automatic Bank Fraud Detection Using Support Vector Machines | Paper | Summary | ||
Week of Nov 22 | Zeng Mingde, Lin Xiaoyu, Fan Joshua, Rao Chen Min | Do Vision Transformers See Like Convolutional Neural Networks? | Paper | Summary | ||
Week of Nov 22 | Justin D'Astous, Waqas Hamed, Stefan Vladusic, Ethan O'Farrell | A Probabilistic Approach to Neural Network Pruning | Paper | Summary | ||
Week of Nov 22 | Cassandra Wong, Anastasiia Livochka, Maryam Yalsavar, David Evans | Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification | Paper | Summary | ||
Week of Nov 29 | Jessie Man Wai Chin, Yi Lin Ooi, Yaqi Shi, Shwen Lyng Ngew | CatBoost: unbiased boosting with categorical features | Paper | Summary | ||
Week of Nov 29 | Eric Anderson, Chengzhi Wang, Kai Zhong, YiJing Zhou | Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks | Paper | |||
Week of Nov 29 | Ethan Cyrenne, Dieu Hoa Nguyen, Mary Jane Sin, Carolyn Wang | |||||
Week of Nov 29 | Bowen Zhang, Tyler Magnus Verhaar, Sam Senko | Deep Double Descent: Where Bigger Models and More Data Hurt | Paper | Summary | ||
Week of Nov 29 | Chun Waan Loke, Peter Chong, Clarice Osmond, Zhilong Li | XGBoost: A Scalable Tree Boosting System | Paper | |||
Week of Nov 22 | Ann Gie Wong, Curtis Li, Hannah Kerr | The Detection of Black Ice Accidents for Preventative Automated Vehicles Using Convolutional Neural Networks | Paper | Summary | ||
Week of Nov 22 | Yuwei Liu, Daniel Mao | Depthwise Convolution Is All You Need for Learning Multiple Visual Domains | Paper | Summary | ||
Week of Nov 29 | Lingshan Wang, Yifan Li, Ziyi Liu | Deep Learning for Extreme Multi-label Text Classification | Paper | Summary | ||
Week of Nov 29 | Kar Lok Ng, Muhan (Iris) Li | |||||
Week of Nov 29 | Kun Wang | Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases | Paper | Summary | ||
Week of Nov 29 | Egemen Guray | Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network | Paper | Summary | ||
Week of Nov 29 | Bsodjahi | Bayesian Network as a Decision Tool for Predicting ALS Disease | Paper | Summary | ||
Week of Nov 29 | Xin Yan, Yishu Duan, Xibei Di | Predicting Hurricane Trajectories Using a Recurrent Neural Network | Paper | Summary | ||
Week of Nov 29 | Ankitha Anugu, Yushan Chen, Yuying Huang | A Game Theoretic Approach to Class-wise Selective Rationalization | Paper | Summary | ||
Week of Nov 29 | Aavinash Syamala, Dilmeet Malhi, Sohan Islam, Vansh Joshi | Research on Multiple Classification Based on Improved SVM Algorithm for Balanced Binary Decision Tree | Paper | Summary | ||
Week of Nov 29 | Christian Mitrache, Alexandra Mossman, Jessica Saini, Aaron Renggli | U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging | [2] | Summary |