projects
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- 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 Ra; Saeed Khodaparast;
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 Shaeesabet: Graph Auto-encoder
projects.1573766229.txt.gz · Last modified: 2019/11/14 21:17 by hj