harmony
发表于 2025-3-27 00:05:16
Matteo Binascouning the same model from scratch for downstream tasks? How to reuse the pruning results of previous tasks to accelerate the pruning for new tasks? To address these challenges, we create a small model for a new task from the pruned models of similar tasks. We show that a few fine-tuning steps on thi
Fraudulent
发表于 2025-3-27 04:28:57
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圆锥体
发表于 2025-3-27 05:19:37
Matteo Binasco losslessly compress the data while including the cost of describing the model itself. While MDL can naturally express the behavior of certain models such as autoencoders (that inherently compress data) most representation learning techniques do not rely on such models. Instead, they learn represent
DNR215
发表于 2025-3-27 13:06:57
Matteo Binascoined devices. Despite their success, BNNs still suffer from a fixed and limited compression factor that may be explained by the fact that existing pruning methods for full-precision DNNs cannot be directly applied to BNNs. In fact, weight pruning of BNNs leads to performance degradation, which sugge
Ledger
发表于 2025-3-27 16:27:20
Matteo Binascobioinformatics. Existing UGAD paradigms often adopt data augmentation techniques to construct multiple views, and then employ different strategies to obtain representations from different views for jointly conducting UGAD. However, most previous works only considered the relationship between nodes/g
极大的痛苦
发表于 2025-3-27 19:15:18
Matteo Binasco active learning strategies aim at minimizing the amount of labelled data required to train a DL model. Most active strategies are based on uncertain sample selection, and even often restricted to samples lying close to the decision boundary. These techniques are theoretically sound, but an understa
音乐会
发表于 2025-3-27 22:04:08
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STELL
发表于 2025-3-28 03:37:00
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APNEA
发表于 2025-3-28 09:37:18
Matteo Binascontations for these two groups of nodes, this paper proposes a degree-aware model named DegUIL to narrow the degree gap. To this end, our model complements missing neighborhoods for tail nodes and discards redundant structural information for super head nodes in embeddings respectively. Specifically,
Hypopnea
发表于 2025-3-28 12:37:12
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