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 1031–1040 of 4891 papers

TitleStatusHype
HTR-JAND: Handwritten Text Recognition with Joint Attention Network and Knowledge DistillationCode0
Graph Learning from Data under Structural and Laplacian ConstraintsCode0
Branches: Efficiently Seeking Optimal Sparse Decision Trees with AO*Code0
GraphGAN: Graph Representation Learning with Generative Adversarial NetsCode0
Graph Construction with Flexible Nodes for Traffic Demand PredictionCode0
Granular Ball Twin Support Vector MachineCode0
Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point ProcessesCode0
Grafting for Combinatorial Boolean Model using Frequent Itemset MiningCode0
Graph Degree Linkage: Agglomerative Clustering on a Directed GraphCode0
Boundary Graph Neural Networks for 3D SimulationsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified