179 citations · 420 across the 27 of their papers we have counts for
10 papers · 1 filter
MLJ: A Julia package for composable machine learning
Anthony D. Blaom, Franz Kiraly, Thibaut Lienart +3
MLJ (Machine Learing in Julia) is an open source software package providing a common interface for interacting with machine learning models written in Julia and other languages. It…
Forecasting with sktime: Designing sktime's New Forecasting API and Applying It to Replicate and Extend the M4 Study
Markus Löning, Franz Király
We present a new open-source framework for forecasting in Python. Our framework forms part of sktime, a more general machine learning toolbox for time series with scikit-learn comp…
A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency
Anthony Bagnall, Franz Király, Markus Löning +2
sktime is an open source, Python based, sklearn compatible toolkit for time series analysis developed by researchers at the University of East Anglia (UEA), University College Lond…
sktime: A Unified Interface for Machine Learning with Time Series
Markus Löning, Anthony Bagnall, Sajaysurya Ganesh +3
We present sktime -- a new scikit-learn compatible Python library with a unified interface for machine learning with time series. Time series data gives rise to various distinct bu…
Machine Learning Automation Toolbox (MLaut)
Viktor Kazakov, Franz J. Király
In this paper we present MLaut (Machine Learning AUtomation Toolbox) for the python data science ecosystem. MLaut automates large-scale evaluation and benchmarking of machine learn…
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature
Franz J Király, Bilal Mateen, Raphael Sonabend
Objective: To determine the completeness of argumentative steps necessary to conclude effectiveness of an algorithm in a sample of current ML/AI supervised learning literature. Dat…
Learning with Cross-Kernels and Ideal PCA
Franz J Király, Martin Kreuzer, Louis Theran
We describe how cross-kernel matrices, that is, kernel matrices between the data and a custom chosen set of `feature spanning points' can be used for learning. The main potential o…
Coherence and sufficient sampling densities for reconstruction in compressed sensing
Franz J. Király, Louis Theran
We give a new, very general, formulation of the compressed sensing problem in terms of coordinate projections of an analytic variety, and derive sufficient sampling rates for signa…
The Algebraic Combinatorial Approach for Low-Rank Matrix Completion
Franz J. Király, Louis Theran, Ryota Tomioka
We present a novel algebraic combinatorial view on low-rank matrix completion based on studying relations between a few entries with tools from algebraic geometry and matroid theor…
A Combinatorial Algebraic Approach for the Identifiability of Low-Rank Matrix Completion
Franz Kiraly, Ryota Tomioka
In this paper, we review the problem of matrix completion and expose its intimate relations with algebraic geometry, combinatorics and graph theory. We present the first necessary…