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 3411–3420 of 4891 papers

TitleStatusHype
Constrained Trajectory Optimization on Matrix Lie Groups via Lie-Algebraic Differential Dynamic Programming—0
Machine Learning for Large-Scale Optimization in 6G Wireless Networks—0
Fast Barrier Option Pricing by the COS BEM Method in Heston Model—0
Adaptive Spiral Layers for Efficient 3D Representation Learning on MeshesCode0
Deep Active Contours for Real-time 6-DoF Object Tracking—0
Temporal-Coded Spiking Neural Networks with Dynamic Firing Threshold: Learning with Event-Driven Backpropagation—0
IHNet: Iterative Hierarchical Network Guided by High-Resolution Estimated Information for Scene Flow EstimationCode0
Deep Video Demoireing via Compact Invertible Dyadic Decomposition—0
Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach—0
Toward Efficient Automated Feature Engineering—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified