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 2761–2770 of 4891 papers

TitleStatusHype
LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem—0
Implementation of soft-constrained MPC for Tracking using its semi-banded problem structure—0
Redefining cystoscopy with ai: bladder cancer diagnosis using an efficient hybrid cnn-transformer model—0
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN—0
Enhancing Price Prediction in Cryptocurrency Using Transformer Neural Network and Technical Indicators—0
Enhanced Low-Dose CT Image Reconstruction by Domain and Task Shifting Gaussian Denoisers—0
D4C Glove-train: Solving the RPM and Bongard-logo Problem by Circumscribing and Building Distribution for Concepts—0
Single-level Robust Bidding of Renewable-only Virtual Power Plant in Energy and Ancillary Service Markets for Worst-case Profit—0
Enhancing Security in Federated Learning through Adaptive Consensus-Based Model Update Validation—0
A consensus-constrained parsimonious Gaussian mixture model for clustering hyperspectral imagesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified