Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Mengdi Huai"'
Publikováno v:
Proceedings of the ACM Web Conference 2023.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b37342e36ef7cbe4271d6301219f6bad
https://doi.org/10.1145/3543507.3583280
https://doi.org/10.1145/3543507.3583280
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:6935-6943
Providing model explanations has gained significant popularity recently. In contrast with the traditional feature-level model explanations, concept-based explanations can provide explanations in the form of high-level human concepts. However, existin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9beccece1692d78cdd094053b1d5764
https://doi.org/10.1609/aaai.v36i6.20651
https://doi.org/10.1609/aaai.v36i6.20651
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 16:1-25
Metric learning aims at automatically learning a distance metric from data so that the precise similarity between data instances can be faithfully reflected, and its importance has long been recognized in many fields. An implicit assumption in existi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1173ee761178e8b7a6bd3597a65e6ddf
https://doi.org/10.1145/3502726
https://doi.org/10.1145/3502726
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3b2537ca019b5b437f388df6977f09b
https://doi.org/10.1109/tkde.2022.3209997
https://doi.org/10.1109/tkde.2022.3209997
Publikováno v:
Proceedings of the 2023 SIAM International Conference on Data Mining (SDM) ISBN: 9781611977653
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73ba4e79aa142a9465a023483bf7054e
https://doi.org/10.1137/1.9781611977653.ch88
https://doi.org/10.1137/1.9781611977653.ch88
Publikováno v:
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fda5b5ef299bffa1771fc3086c3f88a2
https://doi.org/10.1109/bibm55620.2022.9995016
https://doi.org/10.1109/bibm55620.2022.9995016
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc8e1c12527730a8b80f599a3bdced49
https://doi.org/10.1145/3534678.3539298
https://doi.org/10.1145/3534678.3539298
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 14:1-33
The goal of metric learning is to learn a good distance metric that can capture the relationships among instances, and its importance has long been recognized in many fields. An implicit assumption in the traditional settings of metric learning is th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4a1115a29cab82a5186c3af8237cd5d
https://doi.org/10.1145/3364320
https://doi.org/10.1145/3364320
Publikováno v:
AAAI
Inferring effective connectivity between different brain regions from functional magnetic resonance imaging (fMRI) data is an important advanced study in neuroinformatics in recent years. However, current methods have limited usage in effective conne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c303fab82c30b1bdbafacfde7f4d1c28
https://doi.org/10.1609/aaai.v34i04.5921
https://doi.org/10.1609/aaai.v34i04.5921
Publikováno v:
AAAI
Pairwise learning has received much attention recently as it is more capable of modeling the relative relationship between pairs of samples. Many machine learning tasks can be categorized as pairwise learning, such as AUC maximization and metric lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aad0493da7f8d4760934983fe7d3546c
https://doi.org/10.1609/aaai.v34i01.5411
https://doi.org/10.1609/aaai.v34i01.5411