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 4301–4310 of 4891 papers

TitleStatusHype
Efficient MPC for Emergency Evasive Maneuvers, Part I: Hybridization of the Nonlinear Problem—0
Efficient Multi-Task Inferencing: Model Merging with Gromov-Wasserstein Feature Alignment—0
Efficient n-body simulations using physics informed graph neural networks—0
Breast Cancer Histopathology Classification using CBAM-EfficientNetV2 with Transfer Learning—0
Efficient Network Traffic Feature Sets for IoT Intrusion Detection—0
Efficient Neural Ranking using Forward Indexes and Lightweight Encoders—0
Efficient N:M Sparse DNN Training Using Algorithm, Architecture, and Dataflow Co-Design—0
Efficient Object-centric Representation Learning with Pre-trained Geometric Prior—0
Efficient Online Hyperparameter Optimization for Kernel Ridge Regression with Applications to Traffic Time Series Prediction—0
Efficient Optimization Accelerator Framework for Multistate Ising Problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified