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 2611–2620 of 4891 papers

TitleStatusHype
Robust N-1 secure HV Grid Flexibility Estimation for TSO-DSO coordinated Congestion Management with Deep Reinforcement Learning—0
Robust Networked Federated Learning for Localization—0
Robust Object Tracking Based on Self-adaptive Search Area—0
Robust Offline Reinforcement Learning with Linearly Structured f-Divergence Regularization—0
Robust Partially-Compressed Least-Squares—0
Robust PCA Based on Adaptive Weighted Least Squares and Low-Rank Matrix Factorization—0
Robust personalized pricing under uncertainty of purchase probabilities—0
Robust Predictable Control—0
Robust Regularization with Adversarial Labelling of Perturbed Samples—0
Robust Subspace Clustering with Compressed Data—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified