Paper 1, Section I, 7H\mathbf{7 H}

Optimization | Part IB, 2021

(a) Let fi:RdRf_{i}: \mathbb{R}^{d} \rightarrow \mathbb{R} be a convex function for each i=1,,mi=1, \ldots, m. Show that

xmaxi=1,,mfi(x) and xi=1mfi(x)x \mapsto \max _{i=1, \ldots, m} f_{i}(x) \quad \text { and } \quad x \mapsto \sum_{i=1}^{m} f_{i}(x)

are both convex functions.

(b) Fix cRdc \in \mathbb{R}^{d}. Show that if f:RRf: \mathbb{R} \rightarrow \mathbb{R} is convex, then g:RdRg: \mathbb{R}^{d} \rightarrow \mathbb{R} given by g(x)=f(cTx)g(x)=f\left(c^{T} x\right) is convex.

(c) Fix vectors a1,,anRda_{1}, \ldots, a_{n} \in \mathbb{R}^{d}. Let Q:RdRQ: \mathbb{R}^{d} \rightarrow \mathbb{R} be given by

Q(β)=i=1nlog(1+eaiTβ)+j=1dβjQ(\beta)=\sum_{i=1}^{n} \log \left(1+e^{a_{i}^{T} \beta}\right)+\sum_{j=1}^{d}\left|\beta_{j}\right|

Show that QQ is convex. [You may use any result from the course provided you state it.]

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