How to Optimize SVMs
Support Vector Machines (SVMs) are very elegant classical machine learning models before the era of deep learning. I still remember... Continue
How to Optimize Multinomial Logistic Regression
I randomly came to scikit-learn LogisticRegression page and found they might support different regularization terms such as $\ell$-1 norm, squared... Continue
Scalable Low-Rank Tensor Completion
Tensor completion asks us to recover a multidimensional array from only a subset of its entries. A hyperspectral image is... Continue
Robust Structured Multi-Task Regression
Multi-task regression is useful when several prediction problems are related, but not identical. Instead of fitting one independent model for... Continue
Sparse Orthogonality-Constrained Optimization via ADPMM
Optimization problems with orthogonality constraints arise throughout machine learning, including dimensionality reduction, clustering, and representation learning. These problems require the... Continue
Simplex-Constrained Incoherent Matrix Factorization with Hybrid Mirror Descent
Matrix factorization is a fundamental tool in data mining and machine learning, with applications in clustering, topic modeling, recommender systems,... Continue
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