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- Kyoto UniversityJP16 papers
- The University of TokyoJP16 papers
- Tokyo Institute of TechnologyJP7 papers
- University of TsukubaJP6 papers
- National Institute of Advanced Industrial Science and TechnologyJP5 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE3 papers
- Institut polytechnique de GrenobleFR3 papers
- Japan Atomic Energy AgencyJP3 papers
- Kyoto College of Graduate Studies for InformaticsJP3 papers
- Kyushu UniversityJP3 papers
- Nara Institute of Science and TechnologyJP3 papers
Showing 2019 · stat.MLShow all
3 papers · 2 filters
stat.ML2019
Direction Matters: On Influence-Preserving Graph Summarization and Max-cut Principle for Directed Graphs
Wenkai Xu, Gang Niu, Aapo Hyvärinen +1
Summarizing large-scaled directed graphs into small-scale representations is a useful but less studied problem setting. Conventional clustering approaches, which based on "Min-Cut"…
stat.ML2019
Active learning for enumerating local minima based on Gaussian process derivatives
Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura +1
We study active learning (AL) based on Gaussian Processes (GPs) for efficiently enumerating all of the local minimum solutions of a black-box function. This problem is challenging…
stat.ML2019★ 5 cited
Robust Graph Embedding with Noisy Link Weights
Akifumi Okuno, Hidetoshi Shimodaira
We propose -graph embedding for robustly learning feature vectors from data vectors and noisy link weights. A newly introduced empirical moment -score reduces the influence o…