The paper closes the gap between upper and lower bounds on space for streaming attention approximation by combining discrepancy, polynomial, and partitioning techniques for algorithms and a new INDEX-based lower bound method.
Proceedings of the 2017 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA) , chapter =
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Towards Tight Bounds for Streaming Attention
The paper closes the gap between upper and lower bounds on space for streaming attention approximation by combining discrepancy, polynomial, and partitioning techniques for algorithms and a new INDEX-based lower bound method.