EECS6327

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• Project one

• Project Two: Your project 2 report will be submitted as a CS conference paper. You may use any latex temple from CVPR, ACL, ICML, etc. It is expected to be 6-8 pages (double-columned). I will mark your report as a conference reviewer based on format, writing style, work quality, extra additions to the existing methods, etc..

Presentation Schedule for Project Two (tentative):

• Dec 13: Rezaul Karim; Sahar Khorramabadi

• Dec 16: Ali Nasehzadeh; Narges Boroujeni; Hongda Wu; Kavitha Raj

All Topics for Project Two:

1. Kavitha Bakshi: Implementing classifiers to categorize the news based on its content using support vector machines
2. Sahar Seidi Khorramabadi: Credit Card Fraud Detection Using Several Machine Learning Methods
3. Rezaul Karim: Convolutional Feature Pyramid Network with Recurrent Attention
4. Huy Vu: Generating motorbike images using Least Squares Generative Adversarial Networks
5. Md Tanvir Hossan: Reinforcement Learning for User Association and Resource Allocation in Heterogeneous Network
6. Daniel Gleason: Actor Critic Reinforcement Learning for automated parking of differential drive vehicle
7. Ali Nasehzadeh: Deep Reinforcement Learning for Optimal Trade Execution of Bitcoin Cryptocurrency
8. Narges Haghighati Boroujeni: Predicting price changes in stock market using recurrent neural networks
9. Yunge Hao: Use SVMs and Neural Networks to Predict the Successfulness of Movies in IMDB
10. Fengbo Lan: Adversarial training to defend adversarial attacks in MNIST
11. Sheyda Zarandi: Image Classification using Convolutional Neural Network
12. Chenxing Zheng: Single Image Haze Removal Using Deep Learning
13. Hongda Wu: Modulation Recognition Comparison by Using Support Vector Machines and Deep Neural Networks
14. Jonathan Azpur: Deep XGBoost Image Classifier
15. Saeed Khodaparast: Chest abnormality detection on X-ray images using deep neural networks
16. Ali Nematichari: A Comparative study on several machine learning methods for face recognition
17. Behnam Asadi: A Theoretical Study on Approximation Power of Fully Connected Networks with ReLU Activation and Softmax Layer
18. Hamidreza Taleghamar: Network Compression for Deep Neural Networks
19. Mahta Shaeesabet: Graph Auto-encoder