## 辅导案例-ECE 2195

• May 15, 2020

Machine Learning ECE 2195 (Fall 2019) Lecture 5-1 Linear Algebra Review Heng Huang, Ph.D. Department of Electrical and Computer Engineering Linear Algebra Review • Vector-Vector Products – Inner product or dot product – Outer product Fall 2019 Heng Huang Machine Learning 2 Linear Algebra Review • Identity matrix • Diagonal matrix • Transpose Fall 2019 Heng Huang Machine Learning 3 Linear Algebra Review • Symmetric matrix • Trace ? Fall 2019 Heng Huang Machine Learning 4 Linear Algebra Review • Norm Fall 2019 Heng Huang Machine Learning 5 Linear Algebra Review • Inverse: invertible or non-singular • Orthogonal matrix Fall 2019 Heng Huang Machine Learning 6 Linear Algebra Review • Quadratic form i.e., only the symmetric part of A contributes to the quadratic form. For this reason, we often implicitly assume that the matrices appearing in a quadratic form are symmetric. • Positive definite, positive semidefinite, negative definite One important property of positive definite and negative definite matrices is that they are always full rank, and hence, invertible. Fall 2019 Heng Huang Machine Learning 7 Linear Algebra Review • Gram matrix – Positive semidefinite • Eigenvectors and eigenvalues ? ? Fall 2019 Heng Huang Machine Learning 8 Linear Algebra Review • Derivatives of matrix Derivatives of trace • Exercise Fall 2019 Heng Huang Machine Learning 9 Convex Function f(t x + (1-t) y) <= t f(x) + (1-t) f(y) Fall 2019 Heng Huang Machine Learning 10 Convex Set Region above a convex function is a convex set. Fall 2019 Heng Huang Machine Learning 11 Programming • Objective function to be minimized/maximized. • Constraints to be satisfied. Example Objective function Constraints Fall 2019 Heng Huang Machine Learning 12 Convex Programming • Convex optimization function • Convex feasible region • Why is it so important ??? • Global optimum can be found in polynomial time. • Many practical problems are convex • Non-convex problems can be relaxed to convex ones. Fall 2019 Heng Huang Machine Learning 13 Quadratic Programming Fall 2019 Heng Huang Machine Learning 14

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