Automating Data Science The ABC of Data: A Classifying Framework for Data Readiness
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2020 |
Castelijns, Laurens A. |
Towards Automated Configuration of Stream Clustering Algorithms
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2020 |
Carnein, Matthias |
Learning and Interpreting Potentials for Classical Hamiltonian Systems
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2020 |
Bhat, Harish S. |
Measuring Unfairness Through Game-Theoretic Interpretability
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2020 |
Cesaro, Juliana |
Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning
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2020 |
Hegedüs, István |
Decentralized Learning with Budgeted Network Load Using Gaussian Copulas and Classifier Ensembles
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2020 |
Klein, John |
A Comparative Study of Community Detection Techniques for Large Evolving Graphs
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2020 |
Coppens, Lauranne |
Hardware Acceleration of Machine Learning Beyond Linear Algebra
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2020 |
Mücke, Sascha |
Manifold Mixing for Stacked Regularization
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2020 |
Pereira, Joao |
Mobile Game Theory with Street Gangs
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2020 |
Cooney, Sarah |
DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets
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2020 |
Volcker, Claas |
Automating Common Data Science Matrix Transformations
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2020 |
Contreras-Ochando, Lidia |
Learning Parsers for Technical Drawings
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2020 |
Daele, Dries van |
ReinBo: Machine Learning Pipeline Conditional Hierarchy Search and Configuration with Bayesian Optimization Embedded Reinforcement Learning
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2020 |
Sun, Xudong |
The autofeat Python Library for Automated Feature Engineering and Selection
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2020 |
Horn, Franziska |
Global Explanations with Local Scoring
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2020 |
Setzu, Mattia |
Effect of Superpixel Aggregation on Explanations in LIME — A Case Study with Biological Data
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2020 |
Schallner, Ludwig |
Adversarial Robustness Curves
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2020 |
Göpfert, Christina |
Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space
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2020 |
Botari, Tiago |
Distributed Learning of Neural Networks with One Round of Communication
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2020 |
Izbicki, Mike |