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 901–910 of 4891 papers

TitleStatusHype
Advances and Open Challenges in Federated Foundation Models—0
Collaborative Learning with Different Labeling Functions—0
A Novel and Optimal Spectral Method for Permutation Synchronization—0
A Clustering Method with Graph Maximum Decoding Information—0
Collaborative Honeypot Defense in UAV Networks: A Learning-Based Game Approach—0
Collaborative Group Learning—0
A novel active learning-based Gaussian process metamodelling strategy for estimating the full probability distribution in forward UQ analysis—0
Combinatorial Attacks on Binarized Neural Networks—0
A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information—0
Collaborative Deterministic-Probabilistic Forecasting for Real-World Spatiotemporal Systems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified