# Cone programs and self-dual embeddings

This post aims at providing some intuition into cone programs from different perspectives; in particular:

- Equivalence of different formulations of cone programs
- Fenchel duality
- Primal-dual optimality conditions (OC)
- OCs as variational inequalities
- Homogeneous self-dual embeddings (HSDEs)
- OCs for HSDEs

# Projection on the epigraph of the squared Euclidean norm

As a follow-up on the previous post titled Projection on an epigraph, we here discuss how we can project on the epigraph of the squared norm function. Continue reading →

# Convergence of the iterates of the gradient method with constant stepsize

The gradient method with constant step length is the simplest method for solving unconstrained optimisation problems involving a continuously differentiable function with Lipschitz-continuous gradient. The motivation for this post came after reading this Wikipedia article where it is stated that under certain assumptions the sequence converges to a local optimum, but it is no further discussion is provided. Continue reading →

# Pretty convexity result

Where here we discover some interesting facts about continuous convex functions.

We know that a function is convex if

for all and .

We see that if is a continuous function, then an equivalent condition for convexity is that either of the following inequalities holds