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 3851–3875 of 4891 papers

TitleStatusHype
On-edge Multi-task Transfer Learning: Model and Practice with Data-driven Task Allocation—0
Certifiably Robust Interpretation via Renyi Differential Privacy—0
Dispatchable Region for Active Distribution Networks Using Approximate Second-Order Cone Relaxation—0
Learned Global Optimization for Inverse Scattering Problems -- Matching Global Search with Computational Efficiency—0
Computationally efficient spatial rendering of late reverberation in virtual acoustic environments—0
DF-Conformer: Integrated architecture of Conv-TasNet and Conformer using linear complexity self-attention for speech enhancement—0
Domain Adaptation Broad Learning System Based on Locally Linear Embedding—0
Image Classification with CondenseNeXt for ARM-Based Computing PlatformsCode0
Efficient Tensor Contraction via Fast Count Sketch—0
Harmonic Power-Flow Study of Polyphase Grids with Converter-Interfaced Distributed Energy Resources, Part I: Modelling Framework and Algorithm—0
Connection Sensitivity Matters for Training-free DARTS: From Architecture-Level Scoring to Operation-Level Sensitivity Analysis—0
Boundary Graph Neural Networks for 3D SimulationsCode0
Algorithm Unrolling for Massive Access via Deep Neural Network with Theoretical Guarantee—0
Training or Architecture? How to Incorporate Invariance in Neural Networks—0
Pre-Trained Models: Past, Present and Future—0
Precise phase retrieval for propagation-based images using discrete mathematics—0
Quantum Speedup of Natural Gradient for Variational Bayes—0
Ex uno plures: Splitting One Model into an Ensemble of Subnetworks—0
ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs—0
Fast and More Powerful Selective Inference for Sparse High-order Interaction Model—0
End-to-end reconstruction meets data-driven regularization for inverse problemsCode0
Stochastic filtering for multiscale stochastic reaction networks based on hybrid approximationsCode0
Hierarchical Temperature Imaging Using Pseudo-Inversed Convolutional Neural Network Aided TDLAS Tomography—0
Learning Routines for Effective Off-Policy Reinforcement Learning—0
Nonuniform Defocus Removal for Image Classification—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified