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 2381–2390 of 4891 papers

TitleStatusHype
Efficient Convolutional Neural Network Training with Direct Feedback Alignment—0
Efficient Convolutional Forward Modeling and Sparse Coding in Multichannel Imaging—0
Bidirectional Long-Range Parser for Sequential Data Understanding—0
An Autonomous Vision-Based Algorithm for Interplanetary Navigation—0
Accelerating Spherical k-Means—0
Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers—0
Efficient Computation of Relative Pose for Multi-Camera Systems—0
Efficient CNNs via Passive Filter Pruning—0
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling—0
Efficient Classification for Metric Data—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified