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:

1. Sahar Khorramabadi: Credit Card Fraud Detection Using Several Machine Learning Methods
2. Yunge Hao: Use SVMs and Neural Networks to Predict the Successfulness of Movies in IMDB
3. Rezaul Karim: Convolutional Feature Pyramid Network with Recurrent Attention
4. Sheyda Zarandi: Image Classification using Convolutional Neural Network
5. Chenxing Zheng: Single Image Haze Removal Using Deep Learning
6. Fengbo Lan: Adversarial training to defend adversarial attacks in MNIST
7. Huy Vu: Generating motorbike images using Least Squares Generative Adversarial Networks
8. Md Tanvir Hossan: Reinforcement Learning for User Association and Resource Allocation in Heterogeneous Network
9. Daniel Gleason: Actor Critic Reinforcement Learning for automated parking of differential drive vehicle

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