4 accepted papers
$k$-means++ and the related greedy $k$-means++ algorithm are celebrated algorithms that efficiently compute seeds for Lloyd's algorithm. Greedy $k$-means++ is a generalization of $k$-means++ where, in each iteration, a new seed is greedily chosen among multiple $\ell \geq 2$ points sampled, as oppos…
Open Information Extraction (OpenIE) aims to extract structured information in the form of triples from unstructured text, serving as a foundation for various downstream NLP tasks. Despite the success of neural OpenIE models, their dependence on large-scale annotated datasets poses a challenge, part…
The feedback arc set problem is one of the most fundamental and well-studied ranking problems where n objects are to be ordered based on their pairwise comparison. The problem enjoys several efficient approximation algorithms in the offline setting. Unfortunately, online there are strong lower boun…
In the submodular ranking (SR) problem, the input consists of a set of submodular functions defined on a ground set of elements. The goal is to order elements for all the functions to have value above a certain threshold as soon on average as possible, assuming we choose one element per time. The pr…