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 3671–3680 of 4891 papers

TitleStatusHype
E-detectors: a nonparametric framework for sequential change detectionCode0
Multivariate Time Series Forecasting with Latent Graph Inference—0
A Multi-Document Coverage Reward for RELAXed Multi-Document SummarizationCode0
Benchmarking real-time algorithms for in-phase auditory stimulation of low amplitude slow waves with wearable EEG devices during sleep—0
On consistency of constrained spectral clustering under representation-aware stochastic block model—0
Learning Stochastic Parametric Differentiable Predictive Control Policies—0
Multi-Objective System-by-Design for mm-Wave Automotive Radar Antennas—0
HyperPrompt: Prompt-based Task-Conditioning of Transformers—0
Bayesian Sequential Stacking Algorithm for Concurrently Designing Molecules and Synthetic Reaction Networks—0
BlazeNeo: Blazing fast polyp segmentation and neoplasm detectionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified