Matching Networks for One Shot Learning
Learning from a few examples remains a key challenge in machine learning. Despite recent advances in important domains such as vision and language, the standard supervised deep learning paradigm does not offer a satisfactory solution for learning new concepts rapidly from little data. In this work, we employ ideas from metric learning based on deep neural features and from recent advances that aug
自称有識者()が例の副作用100%予測にがんばって答える - 驚異のアニヲタ社会復帰の予備
ちょっとアレなので非公開になりました。 結論 cross validation くらいしよう。
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https://dl.acm.org/citation.cfm?id=2063892
https://dl.acm.org/citation.cfm?id=2487940
Syntactic Tree Kernels for Event-Time Temporal Relation Learning
[PDF]using Tree Kernels for Classifying Temporal Relations between Events
An event ontology construction approach to web crime mining
