烧瓶
发表于 2025-3-25 04:07:59
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弄皱
发表于 2025-3-25 11:35:01
Candice Christiansen,Meg Martinez-Dettamantiommended list and . is the time horizon. This regret upper bound matches the theoretical guarantee for UCB-like algorithm in the same settings. We also conduct a set of simulations comparing .-TS with the state-of-the-art algorithms. The empirical results demonstrate the advantage of our algorithm over existing works.
停止偿付
发表于 2025-3-25 15:41:32
Nicholas Blagden,Jake Jones,Kirsten Wilsonosts (e.g., renting and oil costs). Thus, we propose a group-wise itinerary planning framework to minimize the travel costs for each user in a temporary social network. Experimental results conducted on real-world data sets confirm the efficiency and effectiveness of our proposed framework.
Factual
发表于 2025-3-25 16:12:51
Collaborative Contextual Combinatorial Cascading Thompson Samplingommended list and . is the time horizon. This regret upper bound matches the theoretical guarantee for UCB-like algorithm in the same settings. We also conduct a set of simulations comparing .-TS with the state-of-the-art algorithms. The empirical results demonstrate the advantage of our algorithm over existing works.
DRILL
发表于 2025-3-25 23:50:57
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Transfusion
发表于 2025-3-26 01:09:28
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思想上升
发表于 2025-3-26 06:22:59
https://doi.org/10.1007/978-94-017-6004-1utational complexity of the IoT Device Management Service Selection problem, an alternative heuristic-based approach called GA4MSS is proposed. Two series of experiments have been conducted and the experimental results show the performance of our approaches.
灾难
发表于 2025-3-26 10:07:06
https://doi.org/10.1007/978-3-030-49068-3 the Movielens 20M dataset, the results of the SDAE-BPR, a traditional item-based collaborative filtering model and a user-based collaborative filtering model are compared. It is shown that the SDAE-BPR has higher accuracy. This method improves the accuracy of parameter estimation and the efficiency of model training.
Erythropoietin
发表于 2025-3-26 13:10:34
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多节
发表于 2025-3-26 19:04:37
https://doi.org/10.1007/978-3-319-74479-7ase the performance of our proposed system and studied the performance of the caching algorithm for different real-world scenarios on different mobile phones. We observed that prefetching data improves the performance to some extent; however, it starts to degrade after a certain point depending upon the number of nearby AOIs.