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 3841–3850 of 4891 papers

TitleStatusHype
DCF-ASN: Coarse-to-fine Real-time Visual Tracking via Discriminative Correlation Filter and Attentional Siamese Network—0
K-expectiles clustering—0
RMP2: A Structured Composable Policy Class for Robot Learning—0
Analytically Tractable Inference in Deep Neural Networks—0
Enhancing Medical Image Registration via Appearance Adjustment NetworksCode1
Loosely Synchronized Search for Multi-agent Path Finding with Asynchronous Actions—0
HTMD-Net: A Hybrid Masking-Denoising Approach to Time-Domain Monaural Singing Voice Separation—0
Accumulations of Projections--A Unified Framework for Random Sketches in Kernel Ridge Regression—0
A Hybrid CNN-BiLSTM Voice Activity DetectorCode1
Eigen-spectrograms: An interpretable feature space for bearing fault diagnosis based on artificial intelligence and image processing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified