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 4181–4190 of 4891 papers

TitleStatusHype
Residual Bootstrap Exploration for Bandit Algorithms—0
Langevin DQNCode0
πVAE: a stochastic process prior for Bayesian deep learning with MCMCCode1
Distributed Sketching Methods for Privacy Preserving Regression—0
Fast Fair Regression via Efficient Approximations of Mutual InformationCode0
ACEnet: Anatomical Context-Encoding Network for Neuroanatomy SegmentationCode1
Multi-Vehicle Routing Problems with Soft Time Windows: A Multi-Agent Reinforcement Learning Approach—0
Development of modeling and control strategies for an approximated Gaussian process—0
Learning Flat Latent Manifolds with VAEs—0
Improving the affordability of robustness training for DNNs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified