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 1741–1750 of 4891 papers

TitleStatusHype
Appearance-based Gesture recognition in the compressed domain—0
Adversarial Imitation Learning via Random Search—0
Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix—0
Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation—0
Compression for Better: A General and Stable Lossless Compression Framework—0
Compressing Recurrent Neural Networks for FPGA-accelerated Implementation in Fluorescence Lifetime Imaging—0
A posteriori Trading-inspired Model-free Time Series Segmentation—0
Adversarial Contrastive Learning by Permuting Cluster Assignments—0
Compressed Sensing Based Residual Recovery Algorithms and Hardware for Modulo Sampling—0
Compressed Dynamic Mode Decomposition for Background Modeling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified