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13 de jun. de 2024 · FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation. Federated Learning (FL) enables model development by leveraging data distributed across numerous edge devices without transferring local data to a central server.
14 de jun. de 2024 · In response, we propose a novel approach, Hierarchically Pruned Attention (HiP), which simultaneously reduces the training and inference time complexity from $O(T^2)$ to $O(T \log T)$ and the space complexity from $O(T^2)$ to $O(T)$.
12 de jun. de 2024 · This simplified example illustrates how Grouped Query Attention can efficiently handle longer sequences by dividing them into smaller groups and computing attention within each group.
11 de jun. de 2024 · Multi-head attention eventually simply consists of concatenating the outputs of different predefined attention heads, into a large matrix. Then, it is transformed into a n x d output matrix that matches dimensions with the input.
14 de jun. de 2024 · Modality-agnostic Domain Generalizable Medical Image Segmentation by Multi-Frequency in Multi-Scale Attention. [Code] Diversified and Personalized Multi-rater Medical Image Segmentation.
30 de jun. de 2024 · Figure 1: Attention scores are normalized between 0 and 1. (a) Cross-attention scores for the subject named ”12-24-1920x1080” of Affwild2 dataset. Both the modalities exhibit higher attention scores due to their strong complementary nature (portraying significant expressions). (b) Cross-attention scores of subject named ”21-24-1920x1080 ...
Hace 6 días · How to config sparsity structures. How to support new user defined sparsity structures. In this tutorial we describe how to use DeepSpeed Sparse Attention (SA) and its building-block kernels. The easiest way to use SA is through DeepSpeed launcher.
