61 citations
- The University of TokyoJP18 papers
- Fujitsu (China)CN11 papers
- The University of OsakaJP9 papers
- RIKEN Center for Advanced PhotonicsJP7 papers
- RIKEN Center for Quantum Computing6 papers
- Waseda UniversityJP6 papers
- National Institute of Advanced Industrial Science and TechnologyJP5 papers
- Fujitsu (United Kingdom)GB4 papers
- Fujitsu (United States)US4 papers
- Japan Science and Technology AgencyJP4 papers
- Kyushu UniversityJP4 papers
- University of TsukubaJP4 papers
Showing 2022 · cs.LGShow all
3 papers · 2 filters
cs.LG2022★ 21 cited
Exploring the Whole Rashomon Set of Sparse Decision Trees
Rui Xin, Chudi Zhong, Zhi Chen +3
In any given machine learning problem, there may be many models that could explain the data almost equally well. However, most learning algorithms return only one of these models,…
cs.LG2022
Practical Insights of Repairing Model Problems on Image Classification
Akihito Yoshii, Susumu Tokumoto, Fuyuki Ishikawa
Additional training of a deep learning model can cause negative effects on the results, turning an initially positive sample into a negative one (degradation). Such degradation is…
cs.LG2022★ 11 cited
SapientML: Synthesizing Machine Learning Pipelines by Learning from Human-Written Solutions
Ripon K. Saha, Akira Ura, Sonal Mahajan +6
Automatic machine learning, or AutoML, holds the promise of truly democratizing the use of machine learning (ML), by substantially automating the work of data scientists. However,…