In this paper, we present a novel convex method for the graph-structured sparse recovery. While various structured sparsities can be represented as the graph-structured sparsity, graph- structured ...

Convex optimization is a key tool in computer science, with applications ranging from machine learning to operational research. Due to the fast growth of data sizes, the development of faster ...

This project explores cost-sensitive logistic regression models for binary classification. Traditional logistic regression treats false positives and false negatives equally, which may not align with ...

Lab/Demo: Build a simple logistic regression model Task: Data Exploration Step: 2. Graphing isn't working in several excercises. First encountered as listed above and in Repro steps. So far, the other ...