SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 3901–3910 of 4891 papers

TitleStatusHype
Comprehensive Survey of Model Compression and Speed up for Vision Transformers—0
Compressed Dynamic Mode Decomposition for Background Modeling—0
Compressed Sensing Based Residual Recovery Algorithms and Hardware for Modulo Sampling—0
Compressing Recurrent Neural Networks for FPGA-accelerated Implementation in Fluorescence Lifetime Imaging—0
Compression for Better: A General and Stable Lossless Compression Framework—0
Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix—0
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition—0
On the Complexity of Winner Determination and Strategic Control in Conditional Approval Voting—0
Computational Efficiency in Multivariate Adversarial Risk Analysis Models—0
Computational Efficiency under Covariate Shift in Kernel Ridge Regression—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified