---
author:
- |
    Shuchi Chawla\
    UW-Madison\
    [shuchi@cs.wisc.edu]{}
- |
    Evangelia Gergatsouli\
    UW-Madison\
    [gergatsouli@wisc.edu]{}
- |
    Yifeng Teng\
    UW-Madison\
    [yifengt@cs.wisc.edu]{}
- |
    Christos Tzamos\
    UW-Madison\
    [tzamos@wisc.edu]{}
- |
    Ruimin Zhang\
    UW-Madison\
    [rzhang274@wisc.edu]{}
bibliography:
- 'allrefs.bib'
title: Learning Optimal Search Algorithms from Data
---

Extension to other feasibility constraints {#sec:extensions}
==========================================

In this section we extend the problem in cases where there is a feasibility constraint $\mathcal{F}$, that limits what or how many boxes we can choose. We consider the cases where we are required to select $k$ distinct boxes, and $k$ independent boxes from a matroid. In both cases we design SPA strategies that can be converted to PA. These two variants are described in more detail in subsections \[subsec:generalK\] and \[subsec:matroids\] that follow.
