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Matrix Computations in Machine Learning

Matrix Computations in Machine Learning

This video was recorded at 26th International Conference on Machine Learning (ICML), Montreal 2009. Matrix Computations are ubiquitous in all areas of science and engineering. In this talk, I will first survey some traditional problems in matrix computations and discuss issues that arise in solving them, such as, accuracy, algorithms and software. Then, I will discuss various matrix computation problems that arise in machine learning, especially specialized computations, such as non-negative matrix factorization, multilevel graph clustering and kernel learning. I will conclude with a pointer to resources and a discussion.
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