Collin Leiber

Poisson subspace clustering: focusing on the essentials in count data

Abstract Count data represented as a matrix of non-negative integer values, such as contingency tables, are prevalent across diverse domains. When clustering such data sets, specific methods are required, as generic algorithms often fail to consider their unique distributional pr...

CODAC: Constraint-based Deep Active Clustering

Abstract Constraint-based Deep Active Clustering (CODAC) integrates actively selected pairwise constraints into deep representation learning to efficiently improve existing cluster structures, even under tight query budgets. CODAC encodes the constraint information into the embed...