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 2176–2200 of 4891 papers

TitleStatusHype
Careful Seeding for k-Medois Clustering with Incremental k-Means++ Initialization—0
Carbon-Aware Computing for Data Centers with Probabilistic Performance Guarantees—0
End-to-end View Synthesis for Light Field Imaging with Pseudo 4DCNN—0
An even-load-distribution design for composite bolted joints using a novel circuit model and artificial neural networks—0
A Non-Parametric Bootstrap for Spectral Clustering—0
Accumulations of Projections--A Unified Framework for Random Sketches in Kernel Ridge Regression—0
End-to-End JPEG Decoding and Artifacts Suppression Using Heterogeneous Residual Convolutional Neural Network—0
Can pruning make Large Language Models more efficient?—0
End-to-End Imitation Learning for Optimal Asteroid Proximity Operations—0
Canonical Bayesian Linear System Identification—0
A Neural Network Subgrid Model of the Early Stages of Planet Formation—0
Encoding Categorical Variables with Conjugate Bayesian Models for WeWork Lead Scoring Engine—0
Enabling Fast, Accurate, and Efficient Real-Time Genome Analysis via New Algorithms and Techniques—0
Balancing Privacy, Robustness, and Efficiency in Machine Learning—0
Emulating the interstellar medium chemistry with neural operators—0
Can LLMs Revolutionize the Design of Explainable and Efficient TinyML Models?—0
An Enhancement of Jiang, Z., et al.s Compression-Based Classification Algorithm Applied to News Article Categorization—0
Mitigating the Impact of Noisy Edges on Graph-Based Algorithms via Adversarial Robustness Evaluation—0
Cross-Scan Mamba with Masked Training for Robust Spectral Imaging—0
Empirical Fourier Decomposition: An Accurate Adaptive Signal Decomposition Method—0
Can Foundation Models Really Segment Tumors? A Benchmarking Odyssey in Lung CT Imaging—0
Empirical Comparison between Cross-Validation and Mutation-Validation in Model Selection—0
EmoDM: A Diffusion Model for Evolutionary Multi-objective Optimization—0
Cancer-Net PCa-Seg: Benchmarking Deep Learning Models for Prostate Cancer Segmentation Using Synthetic Correlated Diffusion Imaging—0
Emergent functions of noise-driven spontaneous activity: Homeostatic maintenance of criticality and memory consolidation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified