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Optimal Approximation – Smoothness Tradeoffs for Soft-Max Functions
A soft-max function has two main efficiency measures: (1) approximation ...
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Fair Hierarchical Clustering
As machine learning has become more prevalent, researchers have begun to...
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Sliding Window Algorithms for k-Clustering Problems
The sliding window model of computation captures scenarios in which data...
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Fair Correlation Clustering
In this paper, we study correlation clustering under fairness constraint...
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Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection
Hierarchical Clustering is an unsupervised data analysis method which ha...
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Clustering without Over-Representation
In this paper we consider clustering problems in which each point is end...
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Is a Single Embedding Enough? Learning Node Representations that Capture Multiple Social Contexts
Recent interest in graph embedding methods has focused on learning a sin...
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On a Model for Integrated Information
In this paper we give a thorough presentation of a model proposed by Ton...
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