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pro vyhledávání: '"lsh"'
Autor:
Nie, Xiaonan, Liu, Qibin, Fu, Fangcheng, Zhu, Shenhan, Miao, Xupeng, Li, Xiaoyang, Zhang, Yang, Liu, Shouda, Cui, Bin
Larger transformer models always perform better on various tasks but require more costs to scale up the model size. To efficiently enlarge models, the mixture-of-experts (MoE) architecture is widely adopted, which consists of a gate network and a ser
Externí odkaz:
http://arxiv.org/abs/2411.08446
Autor:
Chen, Zhuoming, Sadhukhan, Ranajoy, Ye, Zihao, Zhou, Yang, Zhang, Jianyu, Nolte, Niklas, Tian, Yuandong, Douze, Matthijs, Bottou, Leon, Jia, Zhihao, Chen, Beidi
Large language models (LLMs) with long context windows have gained significant attention. However, the KV cache, stored to avoid re-computation, becomes a bottleneck. Various dynamic sparse or TopK-based attention approximation methods have been prop
Externí odkaz:
http://arxiv.org/abs/2410.16179
Publikováno v:
PVLDB, 17(9): 2241 - 2254, 2024
Locality-sensitive hashing (LSH) is a well-known solution for approximate nearest neighbor (ANN) search in high-dimensional spaces due to its robust theoretical guarantee on query accuracy. Traditional LSH-based methods mainly focus on improving the
Externí odkaz:
http://arxiv.org/abs/2406.10938
Autor:
Li, Zezheng, Yip, Kingston
This study introduces a novel BERT-LSH model that incorporates Locality Sensitive Hashing (LSH) to approximate the attention mechanism in the BERT architecture. We examine the computational efficiency and performance of this model compared to a stand
Externí odkaz:
http://arxiv.org/abs/2404.08836
We give new data-dependent locality sensitive hashing schemes (LSH) for the Earth Mover's Distance ($\mathsf{EMD}$), and as a result, improve the best approximation for nearest neighbor search under $\mathsf{EMD}$ by a quadratic factor. Here, the met
Externí odkaz:
http://arxiv.org/abs/2403.05041
Autor:
Verma, Bhisham Dev, Pratap, Rameshwar
Locality sensitive hashing (LSH) is a fundamental algorithmic toolkit used by data scientists for approximate nearest neighbour search problems that have been used extensively in many large scale data processing applications such as near duplicate de
Externí odkaz:
http://arxiv.org/abs/2402.07189
With the rapid development of GPU (Graphics Processing Unit) technologies and neural networks, we can explore more appropriate data structures and algorithms. Recent progress shows that neural networks can partly replace traditional data structures.
Externí odkaz:
http://arxiv.org/abs/2310.09806
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Akademický článek
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