Machine Learning

Efficient Smoothing of Dilated Convolutions for Image Segmentation

In this project we introduce low cost methods of improving dilated convolutions in an image segmentation application. We achieve comparable results to state-of-the-art segmentation performance while being computationally more efficient than previously proposed methods.

Collaborative Filtering: Stacking Collaborative Filtering and Neural Networks for Improved Recommendations

For this proejct we leverage matrix factorization and neural network methods to build a recommender system for movies.