61 citations
- The University of TokyoJP4 papers
- Fujitsu (China)CN3 papers
- National Institute of Advanced Industrial Science and TechnologyJP3 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Fujitsu (United Kingdom)GB2 papers
- University of ManchesterGB2 papers
- University of TsukubaJP2 papers
- Aalborg UniversityDK1 paper
- Baidu (China)CN1 paper
- Bank of JapanJP1 paper
- Beijing University of Posts and TelecommunicationsCN1 paper
- Centre de Recherche en Informatique, Signal et Automatique de LilleFR1 paper
9 papers · 1 filter
Open Multi-Access Network Platform with Dynamic Task Offloading and Intelligent Resource Monitoring
Takuji Tachibana, Kazuki Sawada, Hiroyuki Fujii +4
We constructed an open multi-access network platform using open-source hardware and software. The open multi-access network platform is characterized by the flexible utilization of…
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,…
SoccerNet 2022 Challenges Results
Silvio Giancola, Anthony Cioppa, Adrien Deliège +91
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks:…
Multi-objective QUBO Solver: Bi-objective Quadratic Assignment
Mayowa Ayodele, Richard Allmendinger, Manuel López-Ibáñez +1
Quantum and quantum-inspired optimisation algorithms are designed to solve problems represented in binary, quadratic and unconstrained form. Combinatorial optimisation problems are…
Electronic properties of the steps in bilayer Td-WTe2
Mari Ohfuchi, Akihiko Sekine, Manabu Ohtomo +1
Monolayer WTe2 stripes are quantum spin Hall (QSH) insulators. Density functional theory was used for investigating the electronic properties of the stripes and steps in bilayer Td…
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…