param
Multi-ScaleVMamba: HierarchyinHierarchy VisualStateSpaceModel
Our experiments demonstrate that MSVMamba is highly competitive, with the MSVMamba-Tinymodel achieving83.0%
Learning to Solve SMT Formulas
Mislav Balunovic, Pavol Bielik, Martin Vechev
Wephrase the challenge ofsolving SMT formulas asatree search problemwhere ateach step atransformation is applied to the input formula until the formula is solved.
- Europe > Germany > Saxony > Leipzig (0.05)
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- Europe > Switzerland (0.04)
Degradation-Aware Unfolding Half-Shuffle TransformerforSpectralCompressiveImaging
These imaging systems fail to capture dynamic objects. Recently, snapshotcompressiveimaging (SCI)systems [17,18,19]have been developed to capture HSIs at video rate.
Discrimination-aware Channel Pruning for Deep Neural Networks
Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang, Jing Liu, Yong Guo, Qingyao Wu, Junzhou Huang, Jinhui Zhu
Both strategies suffer from some limitations: the former kind is computationally expensive and difficult to converge, whilst the latter kind optimizes the reconstruction error but ignores the discriminative power of channels.
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- Europe > Portugal > Braga > Braga (0.04)
- Europe > Germany > Hesse > Darmstadt Region > Frankfurt (0.04)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Natural Language (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.96)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.67)
