Kernel Probabilistic Distance Clustering
Citation Department of Industrial Engineering, Middle East Technical University, Ankara, Turkey Article Download View Kernel Probabilistic Distance Clustering
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Time-series aggregation for the optimization of energy systems: goals, challenges, approaches, and opportunities
The rising significance of renewable energy increases the importance of representing time-varying input data in energy system optimization studies. Time-series aggregation, which reduces temporal model complexity, has emerged in recent years to address this challenge. We provide a comprehensive review of time-series aggregation for the optimization of energy systems. We show where time series affect … Read more
On the Cluster-aware Supervised Learning (CluSL): Frameworks, Convergent Algorithms, and Applications
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Modeling time-varying operations in complex energy systems optimization problems is often computationally intractable, and time-series input data are thus often aggregated to representative periods. In this work, we introduce a framework for using clustering methods for this purpose, and we compare both conventionally-used methods (k-means, k-medoids, and hierarchical clustering), and shape-based clustering methods (dynamic time … Read more
Clustering and Multifacility Location with Constraints via Distance Function Penalty Method and DC Programming
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Clustering Categories in Support Vector Machines
Support Vector Machines (SVM) is the state-of-the-art in Supervised Classification. In this paper the Cluster Support Vector Machines (CLSVM) methodology is proposed with the aim to reduce the complexity of the SVM classifier in the presence of categorical features. The CLSVM methodology lets categories cluster around their peers and builds an SVM classifier using the … Read more
Reformulation of a model for hierarchical divisive graph modularity maximization
Finding clusters, or communities, in a graph, or network is a very important problem which arises in many domains. Several models were proposed for its solution. One of the most studied and exploited is the maximization of the so called modularity, which represents the sum over all communities of the fraction of edges within these … Read more
A Branch-and-Price Approach to the k-Clustering Minimum Biclique Completion Problem
Given a bipartite graph G = (S , T , E ), we consider the problem of finding k bipartite subgraphs, called clusters, such that each vertex i of S appears in exactly one of them, every vertex j of T appears in each cluster in which at least one of its neighbors appears, and … Read more
Finding optimal realignments in sports leagues using a branch-and-cut-and-price approach
The sports team realignment problem can be modelled as $k$-way equipartition: given a complete graph $K_{n}=(V,E)$, with edge weight $c_{e}$ on each edge, partition the vertices $V$ into $k$ divisions that have exactly $S$ vertices, so as to minimize the total weight of the edges that have both endpoints in the same division. In this … Read more