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10/21/2022
Auto-Encoder Neural Network Incorporating X-Ray Fluorescence Fundamental Parameters with Machine Learning
We consider energy-dispersive X-ray Fluorescence (EDXRF) applications wh...
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10/03/2022
Automatic Neural Network Hyperparameter Optimization for Extrapolation: Lessons Learned from Visible and Near-Infrared Spectroscopy of Mango Fruit
Neural networks are configured by choosing an architecture and hyperpara...
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02/18/2021
Knowledge Hypergraph Embedding Meets Relational Algebra
Embedding-based methods for reasoning in knowledge hypergraphs learn a r...
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08/14/2020
Binarised Regression with Instance-Varying Costs: Evaluation using Impact Curves
Many evaluation methods exist, each for a particular prediction task, an...
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11/12/2019
A Probabilistic Approach for Predicting Landslides by Learning a Self-Aligned Deep Convolutional Model
Landslides are movement of soil and rock under the influence of gravity....
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06/01/2019
Knowledge Hypergraphs: Extending Knowledge Graphs Beyond Binary Relations
Knowledge graphs store facts using relations between pairs of entities. ...
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12/07/2018
Improved Knowledge Graph Embedding using Background Taxonomic Information
Knowledge graphs are used to represent relational information in terms o...
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08/06/2018
Structure Learning for Relational Logistic Regression: An Ensemble Approach
We consider the problem of learning Relational Logistic Regression (RLR)...
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06/26/2018
Record Linkage to Match Customer Names: A Probabilistic Approach
Consider the following problem: given a database of records indexed by n...
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02/13/2018
SimplE Embedding for Link Prediction in Knowledge Graphs
The aim of knowledge graphs is to gather knowledge about the world and p...
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12/07/2017
RelNN: A Deep Neural Model for Relational Learning
Statistical relational AI (StarAI) aims at reasoning and learning in noi...
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07/25/2017
Comparing Aggregators for Relational Probabilistic Models
Relational probabilistic models have the challenge of aggregation, where...
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07/24/2017
Domain Recursion for Lifted Inference with Existential Quantifiers
In recent work, we proved that the domain recursion inference rule makes...
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10/26/2016
New Liftable Classes for First-Order Probabilistic Inference
Statistical relational models provide compact encodings of probabilistic...
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06/28/2016
A Learning Algorithm for Relational Logistic Regression: Preliminary Results
Relational logistic regression (RLR) is a representation of conditional ...
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06/14/2016
Why is Compiling Lifted Inference into a Low-Level Language so Effective?
First-order knowledge compilation techniques have proven efficient for l...
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04/13/2013
Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (1994)
This is the Proceedings of the Tenth Conference on Uncertainty in Artifi...
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07/20/2011