Log In Sign Up

Projections onto the canonical simplex with additional linear inequalities

by   L. Adam, et al.

We consider projections onto the canonical simplex with additional linear inequalities. We mention three cases in the fields of distributionally robust optimization and accuracy at the top where such projections arise. For these specific examples we write the projections as optimization problems and show that they are equivalent to finding a zero of real-valued functions. We prove that these functions are monotonic and in some cases convex. We employ optimization methods with guaranteed convergence and derive their theoretical complexity. We demonstrate that our methods have (almost) linear observed theoretical complexity.


page 1

page 2

page 3

page 4


Local L^2-bounded commuting projections in FEEC

We construct local projections into canonical finite element spaces that...

Complexity of Linear Minimization and Projection on Some Sets

The Frank-Wolfe algorithm is a method for constrained optimization that ...

Staging Human-computer Dialogs: An Application of the Futamura Projections

We demonstrate an application of the Futamura Projections to human-compu...

A Perturbation Bound on the Subspace Estimator from Canonical Projections

This paper derives a perturbation bound on the optimal subspace estimato...

On additive MDS codes with linear projections

We support some evidence that a long additive MDS code over a finite fie...

Global Linear Convergence of Evolution Strategies on More Than Smooth Strongly Convex Functions

Evolution strategies (ESs) are zero-order stochastic black-box optimizat...

Computing zero-dimensional tropical varieties via projections

We present an algorithm for computing zero-dimensional tropical varietie...

Code Repositories