
Periodic seismicity detection without declustering
Any periodic variations of earthquake occurrence rates in response to sm...
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Designing Machine Learning Toolboxes: Concepts, Principles and Patterns
Machine learning (ML) and AI toolboxes such as scikitlearn or Weka are ...
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mlr3proba: An R Package for Machine Learning in Survival Analysis
As machine learning has become increasingly popular over the last few de...
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Kernels for time series with irregularlyspaced multivariate observations
Time series are an interesting frontier for kernelbased methods, for th...
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sktime: A Unified Interface for Machine Learning with Time Series
We present sktime  a new scikitlearn compatible Python library with a...
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Machine Learning Automation Toolbox (MLaut)
In this paper we present MLaut (Machine Learning AUtomation Toolbox) for...
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Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness
Machine learning (ML), artificial intelligence (AI) and other modern sta...
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NIPS  Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature
Objective: To determine the completeness of argumentative steps necessar...
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Modeling outcomes of soccer matches
We compare various extensions of the BradleyTerry model and a hierarchi...
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Probabilistic supervised learning
Predictive modelling and supervised learning are central to modern data ...
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Predictive Independence Testing, Predictive Conditional Independence Testing, and Predictive Graphical Modelling
Testing (conditional) independence of multivariate random variables is a...
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Modelling Competitive Sports: BradleyTerryÉlő Models for Supervised and OnLine Learning of Paired Competition Outcomes
Prediction and modelling of competitive sports outcomes has received muc...
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Kernels for sequentially ordered data
We present a novel framework for kernel learning with sequential data of...
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Prediction and Quantification of Individual Athletic Performance
We provide scientific foundations for athletic performance prediction on...
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Learning with Algebraic Invariances, and the Invariant Kernel Trick
When solving data analysis problems it is important to integrate prior k...
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Matroid Regression
We propose an algebraic combinatorial method for solving large sparse li...
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The Algebraic Approach to Phase Retrieval and Explicit Inversion at the Identifiability Threshold
We study phase retrieval from magnitude measurements of an unknown signa...
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Dualtokernel learning with ideals
In this paper, we propose a theory which unifies kernel learning and sym...
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Efficient Orthogonal Tensor Decomposition, with an Application to Latent Variable Model Learning
Decomposing tensors into orthogonal factors is a wellknown task in stat...
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Obtaining errorminimizing estimates and universal entrywise error bounds for lowrank matrix completion
We propose a general framework for reconstructing and denoising single e...
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Coherence and sufficient sampling densities for reconstruction in compressed sensing
We give a new, very general, formulation of the compressed sensing probl...
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Approximate RankDetecting Factorization of LowRank Tensors
We present an algorithm, AROFAC2, which detects the (CP)rank of a degre...
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The Algebraic Combinatorial Approach for LowRank Matrix Completion
We present a novel algebraic combinatorial view on lowrank matrix compl...
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Algebraic Geometric Comparison of Probability Distributions
We propose a novel algebraic framework for treating probability distribu...
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