Linear Algebra And Optimization With Applications To Machine Learning - Volume Ii: Fundamentals Of Optimization Theory With Applications To Machine LearningAuthor(s): Jean H Gallier, Jocelyn Quaintance\nFormat: Hardback\nPublisher: World Scientific Publishing Co Pte Ltd, Singapore\nImprint: World Scientific Publishing Co Pte Ltd\nISBN-13: 9789811216565, 978-9811216565\nSynopsis\nVolume 2 applies the linear algebra concepts presented in Volume 1 to optimization problems which frequently occur throughout machine learning. This book blends theory with practice by not only carefully discussing the mathematical under pinnings of each optimization technique but by applying these techniques to linear programming, support vector machines (SVM), principal component analysis (PCA), and ridge regression. Volume 2 begins by discussing preliminary concepts of optimization theory such as metric spaces, derivatives, and the Lagrange multiplier technique for finding extrema of real valued functions..