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 4321–4330 of 4891 papers

TitleStatusHype
Reservoir Computing Models for Patient-Adaptable ECG Monitoring in Wearable Devices—0
Some New Results for Poisson Binomial Models—0
Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model—0
Super-Resolution Channel Estimation for Arbitrary Arrays in Hybrid Millimeter-Wave Massive MIMO Systems—0
Efficient Segmentation: Learning Downsampling Near Semantic BoundariesCode0
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning—0
GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity RecognitionCode0
Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling—0
A Targeted Acceleration and Compression Framework for Low bit Neural Networks—0
Quantum-inspired canonical correlation analysis for exponentially large dimensional dataCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified