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Titlebook: Artificial Intelligence; First CAAI Internati Lu Fang,Yiran Chen,Weisheng Dong Conference proceedings 2021 Springer Nature Switzerland AG 2

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edict the opponent’s hand range based on the opponent model and observed action not fold, their additional computation complexity is .(1). The expected win rate algorithm with opponent hand distribution (EWR-HD) is the third method suitable for all rounds which uses the opponent model and observed a
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Philip Bonanno,Abigail Colson,Simon Frenchderation and is thus less conservative and more robust in regards to random scenes. An additional analysis indicates that the proposed SSR performs well on classical metrics. The effectiveness of the proposed SSR model is demonstrated comparing with state-of-the-art methods in unknown scenes.
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Philip Bonanno,Abigail Colson,Simon French data set through the high probability sample selection method. Finally, the two segmented data sets are combined with the labeled data sets to train a scene classifier based on the semi-supervised learning method. To verify the effectiveness of the proposed method, it is further compared with sever
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Philip Bonanno,Abigail Colson,Simon Frenchof entities with the guide of texts, and vice versa. Finally, we introduce the graph convolutional network further to enhance the fusion representation of entities and texts. Extensive experiments on large-scale patent data demonstrate the superior performance of our model on the patent classificati
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