First adversarially robust data structure for c-approximate furthest neighbor search with query time matching the best known oblivious results for many parameter regimes.
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3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
TCM finds provably optimal DNN accelerator mappings by pruning the search space up to 32 orders of magnitude with a new dataplacement concept, delivering 1.2-6.5x better energy-delay-product in 17 seconds instead of hours.
FFM finds optimal fused mappings for tensor accelerators over 10,000 times faster than prior mappers while cutting energy-delay product by up to 1.8x versus hand-tuned designs.
citing papers explorer
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Adversarially Robust Approximate Furthest Neighbor
First adversarially robust data structure for c-approximate furthest neighbor search with query time matching the best known oblivious results for many parameter regimes.
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The Turbo-Charged Mapper: Fast and Optimal Mapping for Energy-efficient and Low-latency Accelerator Design
TCM finds provably optimal DNN accelerator mappings by pruning the search space up to 32 orders of magnitude with a new dataplacement concept, delivering 1.2-6.5x better energy-delay-product in 17 seconds instead of hours.
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Fast and Fusiest: An Optimal Fusion-Aware Mapper for Accelerator Design
FFM finds optimal fused mappings for tensor accelerators over 10,000 times faster than prior mappers while cutting energy-delay product by up to 1.8x versus hand-tuned designs.