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Publication search results
found 12 matches
- 2023
- Toon Calders, Celine Vens, Jefrey Lijffijt, Bart Goethals:
Artificial Intelligence and Machine Learning - 34th Joint Benelux Conference, BNAIC/Benelearn 2022, Mechelen, Belgium, November 7-9, 2022, Revised Selected Papers. Communications in Computer and Information Science 1805, Springer 2023, ISBN 978-3-031-39143-9 [contents] - 2022
- Suzana Basic, Márcio Fuckner, Pascal Wiggers:
Explainable Misinformation Detection from Text: A Critical Look. BNAIC/BENELEARN 2022: 1-15 - Daimy Van Caudenberg, Bart Bogaerts:
Symmetry and Dominance Breaking for Pseudo-Boolean Optimization. BNAIC/BENELEARN 2022: 149-166 - Zhiyi Chen, Marco Loog, Jesse H. Krijthe:
Explaining Two Strange Learning Curves. BNAIC/BENELEARN 2022: 16-30 - Tobias Glasmachers:
Recipe for Fast Large-Scale SVM Training: Polishing, Parallelism, and More RAM! BNAIC/BENELEARN 2022: 31-46 - Kshitij Goyal, Wannes Meert, Hendrik Blockeel, Elia Van Wolputte, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers:
Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming. BNAIC/BENELEARN 2022: 47-64 - Yuko Kato, David M. J. Tax, Marco Loog:
A View on Model Misspecification in Uncertainty Quantification. BNAIC/BENELEARN 2022: 65-77 - Salima Lamsiyah, Christoph Schommer:
A Comparative Study of Sentence Embeddings for Unsupervised Extractive Multi-document Summarization. BNAIC/BENELEARN 2022: 78-95 - Gadzhi Musaev, Kevin Mets, Rokas Tamosiunas, Vadim Uvarov, Tom De Schepper, Peter Hellinckx:
On-device Deep Learning Location Category Inference Model. BNAIC/BENELEARN 2022: 96-111 - Nico Roos:
Specificity and Context Dependent Preferences in Argumentation Systems. BNAIC/BENELEARN 2022: 112-132 - Rolf A. N. Starre, Marco Loog, Frans A. Oliehoek:
Model-Based Reinforcement Learning with State Abstraction: A Survey. BNAIC/BENELEARN 2022: 133-148 - Paul C. Wallbott, Sascha Grollmisch, Thomas Köllmer:
Examining Speaker and Keyword Uniqueness: Partitioning Keyword Spotting Datasets for Federated Learning with the Largest Differencing Method. BNAIC/BENELEARN 2022: 167-177
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