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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2681–2690 of 4891 papers

TitleStatusHype
Online Two-stage Thermal History Prediction Method for Metal Additive Manufacturing of Thin Walls—0
Numerical Derivative-based Flexible Integration Algorithm for Power Electronic Systems Simulation Considering Nonlinear Components—0
Variator: Accelerating Pre-trained Models with Plug-and-Play Compression ModulesCode0
Nested Control Co-design of a Spar Buoy Horizontal-axis Floating Offshore Wind Turbine—0
qPOTS: Efficient batch multiobjective Bayesian optimization via Pareto optimal Thompson samplingCode1
ADMM Algorithms for Residual Network Training: Convergence Analysis and Parallel Implementation—0
Adaptive End-to-End Metric Learning for Zero-Shot Cross-Domain Slot FillingCode0
Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency—0
Studying K-FAC Heuristics by Viewing Adam through a Second-Order LensCode0
Efficient Cross-Task Prompt Tuning for Few-Shot Conversational Emotion Recognition—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified