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 3701–3725 of 4891 papers

TitleStatusHype
Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation—0
Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity—0
Simple is better: Making Decision Trees faster using random sampling—0
A Simple and Efficient Reconstruction Backbone for Snapshot Compressive ImagingCode1
M-ar-K-Fast Independent Component AnalysisCode0
Seismic wave propagation and inversion with Neural Operators—0
Maximizing Influence with Graph Neural Networks—0
An Extensible Benchmark Suite for Learning to Simulate Physical SystemsCode1
Token Shift Transformer for Video ClassificationCode1
Exact Pareto Optimal Search for Multi-Task Learning and Multi-Criteria Decision-Making—0
Value-Agnostic Conversational Semantic Parsing—0
Beyond Sentence-Level End-to-End Speech Translation: Context Helps—0
Multi-scale Matching Networks for Semantic CorrespondenceCode1
Training Energy-Efficient Deep Spiking Neural Networks with Single-Spike Hybrid Input Encoding—0
Learning Span-Level Interactions for Aspect Sentiment Triplet ExtractionCode1
Dissecting FLOPs along input dimensions for GreenAI cost estimationsCode0
HYPER-SNN: Towards Energy-efficient Quantized Deep Spiking Neural Networks for Hyperspectral Image Classification—0
A Frequency-based Parent Selection for Reducing the Effect of Evaluation Time Bias in Asynchronous Parallel Multi-objective Evolutionary Algorithms—0
Dispatch of Virtual Inertia and Damping: Numerical Method with SDP and ADMM—0
Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-β signalingCode0
Logspace Reducibility From Secret Leakage Planted Clique—0
Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare SettingsCode1
Optimal Operation of Power Systems with Energy Storage under Uncertainty: A Scenario-based Method with Strategic Sampling—0
Precision-Weighted Federated Learning—0
Stein Variational Gradient Descent with Multiple Kernel—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified