Zobrazeno 1 - 10
of 490
pro vyhledávání: '"Yew Soon Ong"'
Autor:
Andre K. Y. Low, Flore Mekki-Berrada, Abhishek Gupta, Aleksandr Ostudin, Jiaxun Xie, Eleonore Vissol-Gaudin, Yee-Fun Lim, Qianxiao Li, Yew Soon Ong, Saif A. Khan, Kedar Hippalgaonkar
Publikováno v:
npj Computational Materials, Vol 10, Iss 1, Pp 1-11 (2024)
Abstract The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental
Externí odkaz:
https://doaj.org/article/0fb91db8811d4d46a6d55d2c7d7fdeed
Publikováno v:
Virtual and Physical Prototyping, Vol 15, Iss 3, Pp 340-358 (2020)
Bioprinting is a relatively new and promising tissue engineering approach to solve the problem of donor shortage for organ transplantation. It is a highly-advanced biofabrication system that enables the printing of materials in the form of biomateria
Externí odkaz:
https://doaj.org/article/54b63ba02af546898311ab1e376e2578
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
Externí odkaz:
https://doaj.org/article/3b0b6c995c3044ddbae1fd962c0e3a93
Publikováno v:
IEEE Transactions on Cybernetics. 53:2955-2968
The performance of machine learning algorithms heavily relies on the availability of a large amount of training data. However, in reality, data usually reside in distributed parties such as different institutions and may not be directly gathered and
Publikováno v:
IEEE Internet of Things Journal. 10:5519-5529
Publikováno v:
ACM Transactions on Information Systems. Jan2024, Vol. 42 Issue 1, p1-34. 34p.
Publikováno v:
ACM Transactions on Information Systems. Jan2024, Vol. 42 Issue 1, p1-28. 28p.
Multispace Evolutionary Search for Large-Scale Optimization With Applications to Recommender Systems
Publikováno v:
IEEE Transactions on Artificial Intelligence. 4:107-120
Publikováno v:
IEEE Transactions on Cybernetics. 53:483-496
In dealing with the expensive multiobjective optimization problem, some algorithms convert it into a number of single-objective subproblems for optimization. At each iteration, these algorithms conduct surrogate-assisted optimization on one or multip
Publikováno v:
International Journal of Computer Vision. 130:2994-3013
Contrastive learning has recently shown immense potential in unsupervised visual representation learning. Existing studies in this track mainly focus on intra-image invariance learning. The learning typically uses rich intra-image transformations to