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 901–925 of 4891 papers

TitleStatusHype
Curriculum reinforcement learning for quantum architecture search under hardware errors—0
A Novel Channel Boosted Residual CNN-Transformer with Regional-Boundary Learning for Breast Cancer Detection—0
Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration—0
Advances and Open Challenges in Federated Foundation Models—0
Collaborative Learning with Different Labeling Functions—0
A Novel and Optimal Spectral Method for Permutation Synchronization—0
A Clustering Method with Graph Maximum Decoding Information—0
Combinatorial Attacks on Binarized Neural Networks—0
A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information—0
DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization—0
Curvature Regularized Surface Reconstruction from Point Cloud—0
Combining GCN Structural Learning with LLM Chemical Knowledge for or Enhanced Virtual Screening—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers—0
Combining Retrospective Approximation with Importance Sampling for Optimising Conditional Value at Risk—0
Combining the band-limited parameterization and Semi-Lagrangian Runge--Kutta integration for efficient PDE-constrained LDDMM—0
Collaborative Honeypot Defense in UAV Networks: A Learning-Based Game Approach—0
A novel shape matching descriptor for real-time hand gesture recognition—0
Communication-Efficient Decentralized Federated Learning via One-Bit Compressive Sensing—0
Communication-Efficient Distributed Statistical Inference—0
Communication Optimization for Decentralized Learning atop Bandwidth-limited Edge Networks—0
Community detection by spectral methods in multi-layer networks—0
Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models—0
A numerically efficient output-only system-identification framework for stochastically forced self-sustained oscillators—0
Collaborative Group Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified