
The Curse Revisited: a Newly Quantified Concept of Meaningful Distances for Learning from HighDimensional Noisy Data
Distances between data points are widely used in point cloud representat...
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Adversarial Robustness of Probabilistic Network Embedding for Link Prediction
In today's networked society, many realworld problems can be formalized...
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FONDUE: A Framework for Node Disambiguation Using Network Embeddings
Realworld data often presents itself in the form of a network. Examples...
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ALPINE: Active Link Prediction using Network Embedding
Many realworld problems can be formalized as predicting links in a part...
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Conditional tSNE: Complementary tSNE embeddings through factoring out prior information
Dimensionality reduction and manifold learning methods such as tDistrib...
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ExplaiNE: An Approach for Explaining Network Embeddingbased Link Predictions
Networks are powerful data structures, but are challenging to work with ...
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Conditional Network Embeddings
Network embeddings map the nodes of a given network into ddimensional E...
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Interactive Visual Data Exploration with Subjective Feedback: An InformationTheoretic Approach
Visual exploration of highdimensional realvalued datasets is a fundame...
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Subjectively Interesting Subgroup Discovery on Realvalued Targets
Deriving insights from highdimensional data is one of the core problems...
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Bo Kang
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