为现场
发表于 2025-3-25 04:30:52
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Perineum
发表于 2025-3-25 08:14:46
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Thyroxine
发表于 2025-3-25 15:31:20
https://doi.org/10.1007/978-3-031-45222-2s, we leverage a LSTM-based structure to learn intrinsic temporal dependencies so as to capture the evolution of activity sequences. For in-game behaviors, we develop a time-aware filtering component to better distinguish the behavior patterns occurring in a specific period and a multi-view mechanis
迁移
发表于 2025-3-25 17:54:31
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panorama
发表于 2025-3-25 22:10:22
Massimo Arnone,Tiziana Crovellavel variant of LSTM and a novel attention mechanism. The proposed LSTM is able to learn student profile-aware representation from the heterogeneous behavior sequences. The proposed attention mechanism can dynamically learn the different importance degrees of different days for every student. With mu
同步左右
发表于 2025-3-26 00:47:44
EPARS: Early Prediction of At-Risk Students with Online and Offline Learning Behaviorsrse data. Second, friends of STAR are more likely to be at risk. We constructed a co-occurrence network to approximate the underlying social network and encode the social homophily as features through network embedding. To validate the proposed algorithm, extensive experiments have been conducted am
Cryptic
发表于 2025-3-26 04:29:01
MRMRP: Multi-source Review-Based Model for Rating Predictionng records. MRMRP is capable of extracting useful features from supplementary reviews to further improve recommendation performance by applying a deep learning based method. Moreover, the supplementary reviews can be incorporated into different neural models to boost rating prediction accuracy. Expe
custody
发表于 2025-3-26 09:21:29
Few-Shot Human Activity Recognition on Noisy Wearable Sensor Dataegmentation) have different labels from the bag’s (segmentation’s) label. The prototype is the center of the instances in WPN rather than less discriminative bags, which determines the bag-level classification accuracy. To get the most representative instance-level prototype, we propose two strategi
ALLAY
发表于 2025-3-26 13:01:04
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歹徒
发表于 2025-3-26 17:06:25
Instance Explainable Multi-instance Learning for ROI of Various Datad show that the interpretation issues can be addressed by including a family of utility functions in the space of instance embedding. Following this route, we propose a novel Permutation-Invariant Operator to improve the instance-level interpretability of MIL as well as the overall performance. We a