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 3061–3070 of 4891 papers

TitleStatusHype
Privacy-preserving Multi-biometric Indexing based on Frequent Binary Patterns—0
Efficient Quantification and Representation of Aggregate Flexibility in Electric VehiclesCode0
DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional NetworksCode0
Randomized Dimension Reduction with Statistical Guarantees—0
The Inhibitor: ReLU and Addition-Based Attention for Efficient Transformers—0
An Integer Clustering Approach for Modeling Large-Scale EV Fleets with Guaranteed Performance—0
Variance-Aware Regret Bounds for Stochastic Contextual Dueling BanditsCode0
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor SegmentationCode0
Robustifying State-space Models for Long Sequences via Approximate Diagonalization—0
CoDBench: A Critical Evaluation of Data-driven Models for Continuous Dynamical Systems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified