
Automating Data Science: Prospects and Challenges
Given the complexity of typical data science projects and the associated...
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The KLDivergence between a Graph Model and its Fair IProjection as a Fairness Regularizer
Learning and reasoning over graphs is increasingly done by means of prob...
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CSNE: Conditional Signed Network Embedding
Signed networks are mathematical structures that encode positive and neg...
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DeBayes: a Bayesian method for debiasing network embeddings
As machine learning algorithms are increasingly deployed for highimpact...
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Network Representation Learning for Link Prediction: Are we improving upon simple heuristics?
Network representation learning has become an active research area in re...
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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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Scalable Dyadic Independence Models with Local and Global Constraints
An important challenge in the field of exponential random graphs (ERGs) ...
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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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FACE: Feasible and Actionable Counterfactual Explanations
Work in Counterfactual Explanations tends to focus on the principle of "...
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Discovering Interesting Cycles in Directed Graphs
Cycles in graphs often signify interesting processes. For example, cycli...
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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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An endtoend machine learning system for harmonic analysis of music
We present a new system for simultaneous estimation of keys, chords, and...
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Explicit probabilistic models for databases and networks
Recent work in data mining and related areas has highlighted the importa...
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