4 papers
Online Correlation Clustering with Metric Weights
Sami Davies, Benjamin Moseley, Heather Newman
The standard online version of correlation clustering is prohibitively hard, as even randomized algorithms cannot achieve competitive ratio better than . Prior works bypass t…
Online Correlation Clustering: Simultaneously Optimizing All -norms
Sami Davies, Benjamin Moseley, Heather Newman
The -norm objectives for correlation clustering present a fundamental trade-off between minimizing total disagreements (the -norm) and ensuring fairness to individu…
Matroid-Based TSP Rounding for Half-Integral Solutions
Anupam Gupta, Euiwoong Lee, Jason Li +3
We show how to round any half-integral solution to the subtour-elimination relaxation for the TSP, while losing a less-than-1.5 factor. Such a rounding algorithm was recently given…
Robust Gittins for Stochastic Scheduling
Benjamin Moseley, Heather Newman, Kirk Pruhs +1
A common theme in stochastic optimization problems is that, theoretically, stochastic algorithms need to "know" relatively rich information about the underlying distributions. This…