Fair Representation Clustering with Several Protected Classes

What is it about?

We design algorithms to solve the fair clustering problems. Fair clustering problem occurs frequently in life such as resource allocation. A clustering could be a way to allocate resource where people in the same cluster receive a certain type/amount of resource. Fair clustering ensures that people from each minority groups receive the same resource in total. This means that we don't give people from a certain group too much or too little resource. Algorithms that solve fair clustering problems therefore help to ensure that social resource is allocated in a fair and justice way.

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Why is it important?

Our work gives the first polynomial time constant factor approximation algorithm to fair clustering problem. This means that our algorithm is both fast and accurate. This helps to ensure that social resource is allocated in a fair way.