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

Showing 11011125 of 4891 papers

TitleStatusHype
Granular Ball Twin Support Vector MachineCode0
Graph Construction with Flexible Nodes for Traffic Demand PredictionCode0
Grafting for Combinatorial Boolean Model using Frequent Itemset MiningCode0
Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point ProcessesCode0
Adaptive End-to-End Metric Learning for Zero-Shot Cross-Domain Slot FillingCode0
GLUSE: Enhanced Channel-Wise Adaptive Gated Linear Units SE for Onboard Satellite Earth Observation Image ClassificationCode0
GNNMerge: Merging of GNN Models Without Accessing Training DataCode0
Global Safe Sequential Learning via Efficient Knowledge TransferCode0
Uni-Encoder: A Fast and Accurate Response Selection Paradigm for Generation-Based Dialogue SystemsCode0
Graph Neural Networks for modelling breast biomechanical compressionCode0
An algorithm for two-player repeated games with imperfect public monitoringCode0
GFSNetwork: Differentiable Feature Selection via Gumbel-Sigmoid RelaxationCode0
BEBERT: Efficient and Robust Binary Ensemble BERTCode0
Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry DetectionCode0
Geoseg: A Computer Vision Package for Automatic Building Segmentation and Outline ExtractionCode0
Generative Archimedean CopulasCode0
Efficient Training of Probabilistic Neural Networks for Survival AnalysisCode0
Multiview learning with twin parametric margin SVMCode0
Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement LearningCode0
Geographical Context Matters: Bridging Fine and Coarse Spatial Information to Enhance Continental Land Cover MappingCode0
A Multiscale Environment for Learning by DiffusionCode0
Bayesian sparse reconstruction: a brute-force approach to astronomical imaging and machine learningCode0
GCSAM: Gradient Centralized Sharpness Aware MinimizationCode0
Gaussian Max-Value Entropy Search for Multi-Agent Bayesian OptimizationCode0
GCNv2: Efficient Correspondence Prediction for Real-Time SLAMCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified