Search Results for author:
Found 8 papers, 1 papers with code
Multi-Swap $k$-Means++
The $k$-means++ algorithm of Arthur and Vassilvitskii (SODA 2007) is often the practitioners' choice algorithm for optimizing the popular $k$-means clustering objective and is known to give an $O(\log k)$-approximation in expectation.
A Metaheuristic Algorithm for Large Maximum Weight Independent Set Problems
To solve instances of this size, we develop a new local search algorithm, which is a metaheuristic in the greedy randomized adaptive search (GRASP) framework.
Near-Optimal Correlation Clustering with Privacy
Correlation clustering is a central problem in unsupervised learning, with applications spanning community detection, duplicate detection, automated labelling and many more.
Correlation Clustering in Constant Many Parallel Rounds
Correlation clustering is a central topic in unsupervised learning, with many applications in ML and data mining.
Planar Reachability Under Single Vertex or Edge Failures
In this paper we present an efficient reachability oracle under single-edge or single-vertex failures for planar directed graphs.
Data Structures and Algorithms
Fully Dynamic Consistent Facility Location
This improves over the naive algorithm which consists in recomputing a solution at each time step and that can take up to $O(n^2)$ update time, and $O(n^2)$ total recourse.
Online Reciprocal Recommendation with Theoretical Performance Guarantees
A reciprocal recommendation problem is one where the goal of learning is not just to predict a user's preference towards a passive item (e. g., a book), but to recommend the targeted user on one side another user from the other side such that a mutual interest between the two exists.
Balancing information exposure in social networks
Our goal is to find two sets of nodes to employ in the respective campaigns, so that the overall information exposure for the two campaigns is balanced.
