most citedAuto-Surprise: An Automated Recommender-System (AutoRecSys) Library with Tree of Parzens Estimator (TPE) Optimization

15 citations · 46 across the 11 of their papers we have counts for

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cs.LG20201 cited

Finite Group Equivariant Neural Networks for Games

Oisín Carroll, Joeran Beel

Games such as go, chess and checkers have multiple equivalent game states, i.e. multiple board positions where symmetrical and opposite moves should be made. These equivalences are…

cs.LG20201 cited

Siamese Meta-Learning and Algorithm Selection with 'Algorithm-Performance Personas' [Proposal]

Joeran Beel, Bryan Tyrell, Edward Bergman +2

Automated per-instance algorithm selection often outperforms single learners. Key to algorithm selection via meta-learning is often the (meta) features, which sometimes though do n…

cs.LG20204 cited

Synthetic vs. Real Reference Strings for Citation Parsing, and the Importance of Re-training and Out-Of-Sample Data for Meaningful Evaluations: Experiments with GROBID, GIANT and Cora

Mark Grennan, Joeran Beel

Citation parsing, particularly with deep neural networks, suffers from a lack of training data as available datasets typically contain only a few thousand training instances. Manua…

cs.LG201914 cited

Predicting the Outcome of Judicial Decisions made by the European Court of Human Rights

Conor O'Sullivan, Joeran Beel

In this study, machine learning models were constructed to predict whether judgments made by the European Court of Human Rights (ECHR) would lead to a violation of an Article in th…

cs.LG20192 cited

Multi-stream Data Analytics for Enhanced Performance Prediction in Fantasy Football

Nicholas Bonello, Joeran Beel, Seamus Lawless +1

Fantasy Premier League (FPL) performance predictors tend to base their algorithms purely on historical statistical data. The main problems with this approach is that external facto…

cs.LG2019

Memory-Augmented Neural Networks for Machine Translation

Mark Collier, Joeran Beel

Memory-augmented neural networks (MANNs) have been shown to outperform other recurrent neural network architectures on a series of artificial sequence learning tasks, yet they have…