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 2801–2850 of 4891 papers

TitleStatusHype
Sparse Distance Weighted Discrimination—0
Sparse Exact PGA on Riemannian Manifolds—0
Sparse Imagination for Efficient Visual World Model Planning—0
Sparse Least Squares Low Rank Kernel Machines—0
Cross-token Modeling with Conditional Computation—0
Sparse Optimization for Transfer Learning: A L0-Regularized Framework for Multi-Source Domain Adaptation—0
Sparse Polynomial Chaos expansions using Variational Relevance Vector Machines—0
Sparse Principal Component Analysis via Variable Projection—0
Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory—0
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN—0
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting—0
Spatially Adaptive Cloth Regression with Implicit Neural Representations—0
Spatially Covariant Lesion Segmentation—0
Spatio-temporal Causal Learning for Streamflow Forecasting—0
Spatio-temporal Fourier Transformer (StFT) for Long-term Dynamics Prediction—0
Spatio-temporal point processes with deep non-stationary kernels—0
SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization—0
Speckle Reduction with Trained Nonlinear Diffusion Filtering—0
Spectral Clustering for Discrete Distributions—0
Spectral Densities, Structured Noise and Ensemble Averaging within Open Quantum Dynamics—0
Spectral folding and two-channel filter-banks on arbitrary graphs—0
Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model—0
Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory—0
Spectral Learning of Binomial HMMs for DNA Methylation Data—0
Spectral Machine Learning for Pancreatic Mass Imaging Classification—0
Spectral Motion Alignment for Video Motion Transfer using Diffusion Models—0
SpeechMoE2: Mixture-of-Experts Model with Improved Routing—0
Speech to Text Adaptation: Towards an Efficient Cross-Modal Distillation—0
Speeding up Local Optimization in Vehicle Routing with Tensor-based GPU Acceleration—0
SPEQ: Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning—0
Spherical U-Net on Cortical Surfaces: Methods and Applications—0
SpiDR: A Reconfigurable Digital Compute-in-Memory Spiking Neural Network Accelerator for Event-based Perception—0
Spike-Kal: A Spiking Neuron Network Assisted Kalman Filter—0
SpikePack: Enhanced Information Flow in Spiking Neural Networks with High Hardware Compatibility—0
SpikeSift: A Computationally Efficient and Drift-Resilient Spike Sorting Algorithm—0
SPikE-SSM: A Sparse, Precise, and Efficient Spiking State Space Model for Long Sequences Learning—0
SpINR: Neural Volumetric Reconstruction for FMCW Radars—0
Split Learning for Distributed Collaborative Training of Deep Learning Models in Health Informatics—0
Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifold—0
Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifold—0
SSA-CNN: Semantic Self-Attention CNN for Pedestrian Detection—0
SSD-Poser: Avatar Pose Estimation with State Space Duality from Sparse Observations—0
SSF-PAN: Semantic Scene Flow-Based Perception for Autonomous Navigation in Traffic Scenarios—0
SSL-NBV: A Self-Supervised-Learning-Based Next-Best-View algorithm for Efficient 3D Plant Reconstruction by a Robot—0
SSN: Stockwell Scattering Network for SAR Image Change Detection—0
Randomized Sharpness-Aware Training for Boosting Computational Efficiency in Deep Learning—0
Stability Constrained Mobile Manipulation Planning on Rough Terrain—0
Stabilizing Temporal Difference Learning via Implicit Stochastic Recursion—0
Stacked Generative Machine Learning Models for Fast Approximations of Steady-State Navier-Stokes Equations—0
STARS: Sparse Learning Correlation Filter with Spatio-temporal Regularization and Super-resolution Reconstruction for Thermal Infrared Target Tracking—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified