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Constrained Clustering

Split data into groups, taking into account knowledge in the form of constraints on points, groups of points, or clusters.

Papers

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Showing 51–72 of 72 papers

TitleStatusHype
A Framework for Deep Constrained Clustering -- Algorithms and AdvancesCode1
A Unified Framework for Clustering Constrained Data without Locality Property—0
Faster Balanced Clusterings in High Dimension—0
Approximation Schemes for Low-Rank Binary Matrix Approximation Problems—0
A probabilistic constrained clustering for transfer learning and image category discovery—0
Hierarchical Clustering with Prior Knowledge—0
Clustering With Pairwise Relationships: A Generative Approach—0
Learning to cluster in order to transfer across domains and tasksCode0
Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization—0
Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning—0
A Robust Framework for Classifying Evolving Document Streams in an Expert-Machine-Crowd Setting—0
Leveraging Union of Subspace Structure to Improve Constrained Clustering—0
A constrained clustering based approach for matching a collection of feature sets—0
Semi-supervised Learning with Explicit Relationship Regularization—0
How to Use Temporal-Driven Constrained Clustering to Detect Typical Evolutions—0
Clustering With Side Information: From a Probabilistic Model to a Deterministic Algorithm—0
Iterative Constrained Clustering for Subjectivity Word Sense Disambiguation—0
Fast Computation of Wasserstein BarycentersCode0
Constraints as Features—0
Constrained Clustering and Its Application to Face Clustering in Videos—0
On Constrained Spectral Clustering and Its ApplicationsCode0
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming—0
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