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Titlebook: Advances in Knowledge Discovery and Data Mining; 27th Pacific-Asia Co Hisashi Kashima,Tsuyoshi Ide,Wen-Chih Peng Conference proceedings 202

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Cooperative Control of Linear Systems,two new upper-bound constraints, namely “.” and “.”, to effectively reduce the search space and the computational cost of finding the desired patterns. An efficient neighborhood-aware pattern-growth algorithm has also been presented in this paper to find all GFPs in a database. Experimental results demonstrate that our algorithm is efficient.
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Toward Explainable Recommendation via Counterfactual Reasoningese research gaps by proposing a co-attention-based fine-grained counterfactual explanation model that uses co-attention and aspect representation learning to directly capture user preferences toward different items for recommendation and explanation. The superiority of the proposed model is demonstrated through extensive experiments.
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Preliminaries on Systems Theory,otification allocation with volume constraints. We have conducted both offline and online experiments to evaluate the effectiveness of our method, and the results demonstrate that our approach dramatically improves multiple core metrics of the user experience, such as daily active users.
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Joint Latent Topic Discovery and Expectation Modeling for Financial Marketsn annual return exceeding 10%. This performance surpasses existing benchmarks, setting a new state-of-the-art standard in stock return prediction and multiyear trading simulations (i.e., backtesting).
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