Sparse-aware Maximum Likelihood for Structural Equation ModelsAnhui Huang
此外,我们提供了Visual Transformers的简短概述,因为它们实际上是这项工作中提出的用于处理事件的架构的支柱之一。 Architectures for event-representations processing.旨在处理事件级表示的方法使用利用事件稀疏性的架构处理每个时间窗口内的信息,例如脉冲神经网络[23, 39, 50]、PointNet风格的网络[47]或图神经网络[5, 6...
DeepSparse Sparsity-aware deep learning inference runtime for CPUs DeepSparse is a CPU inference runtime that takes advantage of sparsity to accelerate neural network inference. Coupled with SparseML, our optimization library for pruning and quantizing your models, DeepSparse delivers exceptional infere...
利用sparse learnable spatial-aware part queries来编码局部空间特征。具体来说,提出了Spatial Part Embedding Generation Module(SPEGM),通过局部空间注意机制生成spatial-sensitive part embeddings,它保留了局部空间特征,以增强part-level queries。 我们进一步引入了Selective Iteration Module(SIM),to adaptively update the...
A novel encoding and spatially aware physical design framework (SPARSE) are then proposed that co-optimize the FSM encoding and state FF placement to minimize LFI susceptibility. SPARSE's encoding uses the minimum number of FFs by placing security-sensitive FFs a sufficient distance apart from ...
current sparse adversarial attack methods still have some shortcomings on both sparsity and invisibility. In this paper, we propose a novel two-stage distortion-aware greedy-based method dubbed as “GreedyFool”. Specifically, it first selects the most effective candidate positions to modify b...
This repository provides the code for the paper FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference.FlexPrefill is selected as Oral Presentation(1.77%) at ICLR 2025!TL;DRFlexPrefill is a dynamic and context-aware sparse attention mechanism that optimizes comp...
with pruning-aware sparse regularization. MaskSparsity imposes the fine-grained sparse regularization on the specific filters selected by a pruning mask, rather than all the filters of the model. Before the fine-grained sparse regularization of MaskSparity, we can use many methods to get the prunin...
Recently, integrating video foundation models and large language models to build a video understanding system can overcome the limitations of specific pre-defined vision tasks. Yet, existing methods either employ complex spatial-temporal modules or rely heavily on additional perception models to extract ...
Sparsity-aware deep learning inference runtime for CPUs DeepSparseis a CPU inference runtime that takes advantage of sparsity to accelerate neural network inference. Coupled withSparseML, our optimization library for pruning and quantizing your models, DeepSparse delivers exceptional inference performance ...