2 citations · 2 across the 13 of their papers we have counts for
3 papers · 1 filter
Fair Polylog-Approximate Low-Cost Hierarchical Clustering
Marina Knittel, Max Springer, John Dickerson +1
Research in fair machine learning, and particularly clustering, has been crucial in recent years given the many ethical controversies that modern intelligent systems have posed. Ah…
An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin +1
We present an oracle-efficient relaxation for the adversarial contextual bandits problem, where the contexts are sequentially drawn i.i.d from a known distribution and the cost seq…
Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost
Marina Knittel, Max Springer, John P. Dickerson +1
Clustering is a fundamental building block of modern statistical analysis pipelines. Fair clustering has seen much attention from the machine learning community in recent years. We…