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05/22/2023
AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection
Most anomaly detection systems try to model normal behavior and assume a...
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03/02/2023
DeepSaDe: Learning Neural Networks that Guarantee Domain Constraint Satisfaction
As machine learning models, specifically neural networks, are becoming i...
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10/04/2022
Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming
Internet based businesses and products (e.g. e-commerce, music streaming...
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08/15/2022
Combining Predictions under Uncertainty: The Case of Random Decision Trees
A common approach to aggregate classification estimates in an ensemble o...
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12/01/2021
SaDe: Learning Models that Provably Satisfy Domain Constraints
With increasing real world applications of machine learning, models are ...
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07/11/2020
Feature Interactions in XGBoost
In this paper, we investigate how feature interactions can be identified...
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09/11/2019
LazyBum: Decision tree learning using lazy propositionalization
Propositionalization is the process of summarizing relational data into ...
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03/29/2019
Learning Relational Representations with Auto-encoding Logic Programs
Deep learning methods capable of handling relational data have prolifera...
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05/02/2018
COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series
Clustering is ubiquitous in data analysis, including analysis of time se...
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03/29/2018
COBRAS: Fast, Iterative, Active Clustering with Pairwise Constraints
Constraint-based clustering algorithms exploit background knowledge to c...
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01/30/2018
COBRA: A Fast and Simple Method for Active Clustering with Pairwise Constraints
Clustering is inherently ill-posed: there often exist multiple valid clu...
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05/16/2017
Demystifying Relational Latent Representations
Latent features learned by deep learning approaches have proven to be a ...
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09/23/2016
Constraint-Based Clustering Selection
Semi-supervised clustering methods incorporate a limited amount of super...
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06/28/2016
Theory reconstruction: a representation learning view on predicate invention
With this positional paper we present a representation learning view on ...
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06/28/2016
Clustering-Based Relational Unsupervised Representation Learning with an Explicit Distributed Representation
The goal of unsupervised representation learning is to extract a new rep...
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04/29/2016
An expressive dissimilarity measure for relational clustering using neighbourhood trees
Clustering is an underspecified task: there are no universal criteria fo...
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02/04/2014
Lifted Variable Elimination: Decoupling the Operators from the Constraint Language
Lifted probabilistic inference algorithms exploit regularities in the st...
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06/04/2013
First-Order Decomposition Trees
Lifting attempts to speed up probabilistic inference by exploiting symme...
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08/19/2012
