
Predicting DrugDrug Interactions from Heterogeneous Data: An Embedding Approach
Predicting and discovering drugdrug interactions (DDIs) using machine l...
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Interventional SumProduct Networks: Causal Inference with Tractable Probabilistic Models
While probabilistic models are an important tool for studying causality,...
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Bridging Graph Neural Networks and Statistical Relational Learning: Relational OneClass GCN
We consider the problem of learning Graph Convolutional Networks (GCNs) ...
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Relational Boosted Bandits
Contextual bandits algorithms have become essential in realworld user i...
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Fitted QLearning for Relational Domains
We consider the problem of Approximate Dynamic Programming in relational...
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Knowledge Graph Alignment using String Edit Distance
In this work, we propose a novel knowledge base alignment technique base...
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A Preliminary Approach for Learning Relational Policies for the Management of Critically Ill Children
The increased use of electronic health records has made possible the aut...
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NonParametric Learning of Lifted Restricted Boltzmann Machines
We consider the problem of discriminatively learning restricted Boltzman...
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Lifted Hybrid Variational Inference
A variety of lifted inference algorithms, which exploit model symmetry t...
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NonParametric Learning of Gaifman Models
We consider the problem of structure learning for Gaifman models and lea...
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User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams
One of the key advantages of Inductive Logic Programming systems is the ...
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OneShot Induction of Generalized Logical Concepts via Human Guidance
We consider the problem of learning generalized firstorder representati...
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Predicting DrugDrug Interactions from Molecular Structure Images
Predicting and discovering drugdrug interactions (DDIs) is an important...
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Neural Networks for Relational Data
While deep networks have been enormously successful over the last decade...
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Knowledgeaugmented Column Networks: Guiding Deep Learning with Advice
Recently, deep models have had considerable success in several tasks, es...
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HumanGuided Learning of Column Networks: Augmenting Deep Learning with Advice
Recently, deep models have been successfully applied in several applicat...
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Structure Learning for Relational Logistic Regression: An Ensemble Approach
We consider the problem of learning Relational Logistic Regression (RLR)...
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PreferenceGuided Planning: An Active Elicitation Approach
Planning with preferences has been employed extensively to quickly gener...
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SumProduct Networks for Hybrid Domains
While all kinds of mixed data from personal data, over panel and scient...
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Application of Statistical Relational Learning to Hybrid Recommendation Systems
Recommendation systems usually involve exploiting the relations among kn...
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Learning Relational Dependency Networks for Relation Extraction
We consider the task of KBP slot filling  extracting relation informat...
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Counting Belief Propagation
A major benefit of graphical models is that most knowledge is captured i...
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Sriraam Natarajan
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