A Scalable Multiclass Algorithm for Node Classification
We introduce a scalable algorithm, MUCCA, for multiclass node classification in weighted graphs. Unlike previously proposed methods for the same task, MUCCA works in time linear in the number of nodes. Our approach is based on a game-theoretic formulation of the problem in which the test labels are expressed as a Nash Equilibrium of a certain game. However, in order to achieve scalability, we find the equilibrium on a spanning tree of the original graph. Experiments on real-world data reveal that MUCCA is much faster than its competitors while achieving a similar predictive performance.
Code (3)
Tasks
ClassificationNode ClassificationSimilar Papers 제목 키워드 기반
Incorporating Structural Alternatives and Sharing into Hierarchy for Multiclass Object Recognition and Detection
This paper proposes a reconfigurable model to recognize and detect multiclass (or multiview) objects with large variation in appearance. Compared with well acknowledged hierarchical models, we study two advanced capabili…
Object RecognitionvalidEfficient Large-Scale Structured Learning
We introduce an algorithm, SVM-IS, for structured SVM learning that is computationally scalable to very large datasets and complex structural representations. We show that structured learning is at least as fast-and ofte…
Binary ClassificationClassificationGeneral Classificationobject-detection+1Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification
In hierarchical classification, the prediction paths may be required to always end at leaf nodes. This is called mandatory leaf node prediction (MLNP) and is particularly useful when the leaf nodes have much stronger sem…
ClassificationGeneral ClassificationPredictionMulticlass Optimal Classification Trees with SVM-splits
In this paper we present a novel mathematical optimization-based methodology to construct tree-shaped classification rules for multiclass instances. Our approach consists of building Classification Trees in which, except…
BenchmarkingClassificationMexican Hat Wavelet Kernel ELM for Multiclass Classification
Kernel extreme learning machine (KELM) is a novel feedforward neural network, which is widely used in classification problems. To some extent, it solves the existing problems of the invalid nodes and the large computatio…
ClassificationGeneral Classification